Post - Doc Machine Learning Engineer, Engineering, Science, Physics, Computing, PhD, MSc, BSc, ML, £depending on experience + benefits, Cambridge
This unique and entrepreneurial R&D Company are not your everyday organisation. They cleverly brought together probably some of the smartest scientists, academics and engineers as well as being a fun and rewarding place to work. Their history is an impressive one starting out with just a number of people they have recently been named in a number of media sources as a company to watch out for.
If you really are looking to be challenged not only mathematically but on a day to basis with a number of complex tasks then this could be the job for you.
They currently have some of the brightest academics working for them, however, they realise that everyone is different and company culture is at the core of what they do.
For the Machine Learning Engineer job we like to have the chance to speak to candidates with strong academic backgrounds including Post-Doc's holding a 2.1 or better from a highly ranking university with a degree in a scientific, mathematical, computing or engineering field, outstanding mathematical capabilities is a must, proven knowledge working with Machine Learning, distributed computing, being involved with actual deployment, familiar with Linux and excellent coding abilities in C++, Java or Python.
Naturally for a job like this we please ask that are a detailed person with first class analytical capabilities too, the more detailed your CV with examples then the better.
This job would fit someone looking to work alongside other bright individuals in the Data Science team, Data Storage, processing, Developing Machine Learning Pipelines and assisting with high performing real-time models.Great offices, smart benefits including team outings throughout the year and more!
This company was founded by some of the cleverest academics so this is an opportunity not to be missed.Sound good?
Feel free to apply via the link and we are happy to speak to you on 01223 365197.
Please be assured that your CV will be treated in the strictest confidence and we would always speak to you before discussing your CV with any potential employer.
Please note we are on the client's supplier list for this position.
MODIS are operating as an Employment Agency. MODIS are an equal opportunities employer
Keywords - Job, Post-Doc, PhD, BSc, C++, Java, Python, Linux, Cambridge, Technology, Degree, Engineer, Mathematics, Physics, Science
Modis International Ltd acts as an employment agency for permanent recruitment and an employment business for the supply of temporary workers. Modis International Ltd UK is an Equal Opportunities Employer.
By applying for this role your details will be submitted to Modis. Our Candidate Privacy Information Statement explains how we will use your information - please copy and paste the following link in to your browser: www.modis.co.uk/candidate-privacy-information-statement
13/11/2018
Full time
Post - Doc Machine Learning Engineer, Engineering, Science, Physics, Computing, PhD, MSc, BSc, ML, £depending on experience + benefits, Cambridge
This unique and entrepreneurial R&D Company are not your everyday organisation. They cleverly brought together probably some of the smartest scientists, academics and engineers as well as being a fun and rewarding place to work. Their history is an impressive one starting out with just a number of people they have recently been named in a number of media sources as a company to watch out for.
If you really are looking to be challenged not only mathematically but on a day to basis with a number of complex tasks then this could be the job for you.
They currently have some of the brightest academics working for them, however, they realise that everyone is different and company culture is at the core of what they do.
For the Machine Learning Engineer job we like to have the chance to speak to candidates with strong academic backgrounds including Post-Doc's holding a 2.1 or better from a highly ranking university with a degree in a scientific, mathematical, computing or engineering field, outstanding mathematical capabilities is a must, proven knowledge working with Machine Learning, distributed computing, being involved with actual deployment, familiar with Linux and excellent coding abilities in C++, Java or Python.
Naturally for a job like this we please ask that are a detailed person with first class analytical capabilities too, the more detailed your CV with examples then the better.
This job would fit someone looking to work alongside other bright individuals in the Data Science team, Data Storage, processing, Developing Machine Learning Pipelines and assisting with high performing real-time models.Great offices, smart benefits including team outings throughout the year and more!
This company was founded by some of the cleverest academics so this is an opportunity not to be missed.Sound good?
Feel free to apply via the link and we are happy to speak to you on 01223 365197.
Please be assured that your CV will be treated in the strictest confidence and we would always speak to you before discussing your CV with any potential employer.
Please note we are on the client's supplier list for this position.
MODIS are operating as an Employment Agency. MODIS are an equal opportunities employer
Keywords - Job, Post-Doc, PhD, BSc, C++, Java, Python, Linux, Cambridge, Technology, Degree, Engineer, Mathematics, Physics, Science
Modis International Ltd acts as an employment agency for permanent recruitment and an employment business for the supply of temporary workers. Modis International Ltd UK is an Equal Opportunities Employer.
By applying for this role your details will be submitted to Modis. Our Candidate Privacy Information Statement explains how we will use your information - please copy and paste the following link in to your browser: www.modis.co.uk/candidate-privacy-information-statement
Imagine turning your passion for Data Science, Machine Learning and Artificial Intelligence into insights, predictions and actions that could help develop medicines that change lives. Pushing the frontiers of innovation. Collaborating with some of the finest minds in their fields. Working in an environment that stimulates your curiosity, and enables you to develop your expertise and reach your potential.
AstraZeneca is a global, science led biopharmaceutical business and our innovative medicines are used by millions of patients worldwide. Artificial Intelligence (AI), including deep learning (computer algorithms inspired by biological neural networks), is revolutionising all stages of drug discovery and development from drug design to pivotal clinical trials and beyond. At AstraZeneca, we are deploying AI across the drug discovery phases to discover new connections between data, provide novel insights, accelerate scientific understanding, and increase productivity. For example, we are using AI to help design and synthesise new drug molecules, analyse and interpret the vast amount of data from imaging studies, and for biomarker research to match the right drug to the right patient. In our clinical trials, AI is also enabling us to continuously monitor incoming safety data and alert our scientists to safety signals that need attention.
As a Data Scientist and AI Graduate you will help our scientists make their data ‘AI-ready’, and integrate the latest AI advances into all our drug development programmes. Together we will harness the power of our data and AI to deliver life-changing medicines to patients worldwide.
What does the programme involve?
Your two-year programme begins with an introduction to drug discovery, and how we harness the potential of Data Science, Machine Learning and Artificial Intelligence. You’ll then select two eight-month placements where you’ll apply your developing skills and experience to help us overcome challenges in some of our active research projects. Your placements will help you develop your technical skills and industry knowledge, and on our Global Graduate Development Programme you’ll develop the interpersonal and business skills that will set you up for success.Throughout the programme you’ll work alongside our experts, and take advantage of our close collaborations with leading international academic institutions and organisations to deliver work with real impact.
Placements could involve…
Applying the latest techniques in machine learning and artificial intelligence to preclinical data from drug projects to help detect and understand safety risks and guide the development of new medicines. Exciting work which could also help us refine, reduce and replace animal experiments.
Combining innovative de novo molecule design methodologies utilizing state-of-the-art artificial intelligent technologies with chemistry automation to design novel molecules of therapeutic interest.
Working with our Quantitative Clinical Pharmacology Team to optimize clinical development programs using Bayesian statistic and machine learning modelling.
Developing Bayesian machine learning models for predicting the mechanism and probability of drug toxicity in liver, heart, and other organs. Incorporating existing knowledge of causal relationships and toxicity mechanisms into the prediction problem, and applying Bayesian models to account for uncertainty to improve predictions.
Contributing to challenging projects using advanced Machine Learning models to improve drug discovery by generating testable hypotheses about targets, predicting compound properties, automating complex decision-making processes, and turning data into knowledge.
Applying Artificial Intelligence to integrated electronic health records and genomic data to redefine cancers and help improve patient outcomes.
Working with our Data & Analytics Team to identify, assess and recommend the most innovative external partners, and high impact AI technologies. Writing algorithms to support next generation natural language processing, and optimising code to enable powerful predictive models to be used across AstraZeneca.
As a Data Sciences and AI Graduate you’ll discover how we’re pioneering more open innovation, and actively sharing knowledge and ideas to make the next scientific breakthrough.
Essential Qualification and Skills required:
Highly numerate with a strong Maths, Physics, Statistics or Computer Science focused Bachelors or Masters level qualification gained in 2018 or 2019.
A postgraduate qualification in Data Science, Machine Learning, Artificial Intelligence, Computational Biology, Computational Chemistry, Bioinformatics or Cheminformatics would be advantageous, but is not essential.
Innovative thinking, with enthusiasm, energy and drive.
Open-minded, and ready to embrace new ideas and different perspectives.
Strong critical thinking, planning, organisational and time management skills.
Ability to work as part of a collaborative team that focuses unequivocally on patient needs.
AstraZeneca is an equal opportunity employer. AstraZeneca will consider all qualified applicants for employment without discrimination on grounds of disability, sex or sexual orientation, pregnancy or maternity leave status, race or national or ethnic origin, age, religion or belief, gender identity or re-assignment, marital or civil partnership status, protected veteran status (if applicable) or any other characteristic protected by law.
Please note that our Assessment Centres will be in Gothenburg, Sweden on 26th of April 2019
Applications open: 8th October 2018
Applications close: 27th January 2019
Date Posted: 08-Oct-2018
Closing Date: 27-Jan-2019
22/10/2018
Full time
Imagine turning your passion for Data Science, Machine Learning and Artificial Intelligence into insights, predictions and actions that could help develop medicines that change lives. Pushing the frontiers of innovation. Collaborating with some of the finest minds in their fields. Working in an environment that stimulates your curiosity, and enables you to develop your expertise and reach your potential.
AstraZeneca is a global, science led biopharmaceutical business and our innovative medicines are used by millions of patients worldwide. Artificial Intelligence (AI), including deep learning (computer algorithms inspired by biological neural networks), is revolutionising all stages of drug discovery and development from drug design to pivotal clinical trials and beyond. At AstraZeneca, we are deploying AI across the drug discovery phases to discover new connections between data, provide novel insights, accelerate scientific understanding, and increase productivity. For example, we are using AI to help design and synthesise new drug molecules, analyse and interpret the vast amount of data from imaging studies, and for biomarker research to match the right drug to the right patient. In our clinical trials, AI is also enabling us to continuously monitor incoming safety data and alert our scientists to safety signals that need attention.
As a Data Scientist and AI Graduate you will help our scientists make their data ‘AI-ready’, and integrate the latest AI advances into all our drug development programmes. Together we will harness the power of our data and AI to deliver life-changing medicines to patients worldwide.
What does the programme involve?
Your two-year programme begins with an introduction to drug discovery, and how we harness the potential of Data Science, Machine Learning and Artificial Intelligence. You’ll then select two eight-month placements where you’ll apply your developing skills and experience to help us overcome challenges in some of our active research projects. Your placements will help you develop your technical skills and industry knowledge, and on our Global Graduate Development Programme you’ll develop the interpersonal and business skills that will set you up for success.Throughout the programme you’ll work alongside our experts, and take advantage of our close collaborations with leading international academic institutions and organisations to deliver work with real impact.
Placements could involve…
Applying the latest techniques in machine learning and artificial intelligence to preclinical data from drug projects to help detect and understand safety risks and guide the development of new medicines. Exciting work which could also help us refine, reduce and replace animal experiments.
Combining innovative de novo molecule design methodologies utilizing state-of-the-art artificial intelligent technologies with chemistry automation to design novel molecules of therapeutic interest.
Working with our Quantitative Clinical Pharmacology Team to optimize clinical development programs using Bayesian statistic and machine learning modelling.
Developing Bayesian machine learning models for predicting the mechanism and probability of drug toxicity in liver, heart, and other organs. Incorporating existing knowledge of causal relationships and toxicity mechanisms into the prediction problem, and applying Bayesian models to account for uncertainty to improve predictions.
Contributing to challenging projects using advanced Machine Learning models to improve drug discovery by generating testable hypotheses about targets, predicting compound properties, automating complex decision-making processes, and turning data into knowledge.
Applying Artificial Intelligence to integrated electronic health records and genomic data to redefine cancers and help improve patient outcomes.
Working with our Data & Analytics Team to identify, assess and recommend the most innovative external partners, and high impact AI technologies. Writing algorithms to support next generation natural language processing, and optimising code to enable powerful predictive models to be used across AstraZeneca.
As a Data Sciences and AI Graduate you’ll discover how we’re pioneering more open innovation, and actively sharing knowledge and ideas to make the next scientific breakthrough.
Essential Qualification and Skills required:
Highly numerate with a strong Maths, Physics, Statistics or Computer Science focused Bachelors or Masters level qualification gained in 2018 or 2019.
A postgraduate qualification in Data Science, Machine Learning, Artificial Intelligence, Computational Biology, Computational Chemistry, Bioinformatics or Cheminformatics would be advantageous, but is not essential.
Innovative thinking, with enthusiasm, energy and drive.
Open-minded, and ready to embrace new ideas and different perspectives.
Strong critical thinking, planning, organisational and time management skills.
Ability to work as part of a collaborative team that focuses unequivocally on patient needs.
AstraZeneca is an equal opportunity employer. AstraZeneca will consider all qualified applicants for employment without discrimination on grounds of disability, sex or sexual orientation, pregnancy or maternity leave status, race or national or ethnic origin, age, religion or belief, gender identity or re-assignment, marital or civil partnership status, protected veteran status (if applicable) or any other characteristic protected by law.
Please note that our Assessment Centres will be in Gothenburg, Sweden on 26th of April 2019
Applications open: 8th October 2018
Applications close: 27th January 2019
Date Posted: 08-Oct-2018
Closing Date: 27-Jan-2019
About the role
This will sit within our established Consumer Insights and Analytics team and will help build marketing capability and improve product development with machine learning techniques. The role encompasses orchestrating how the company uses both internal and external large/semi-structured/unstructured data to predict future R&D opportunities as well as real-time algorithms to deliver personalised marketing and web experiences.
About Consumer Insights & Analytics at Abcam
The goal of the Consumer Insights and Analytics team is to catalyse growth across Abcam by helping the organization to transform consumer data into products and initiatives that help life scientists achieve their mission, faster.We are a team of market research, market intelligence, data analyst and data scientist specialists who enjoy working together and in our specialist areas to solve novel and knotty questions for the organisation. We are a growing team with lots of opportunities to influence the business and extend and utilize your skills across a wide range of areas.
Roles & responsibilities:
Encourage the use of data science and data-driven decision-making in the larger organisation.
Innovate and implement machine learning algorithms that discover actionable patterns or inform hypotheses and insights.
Clean and link complex datasets.
Innovate and provide solutions for the business. Some of the problems encountered may be solved immediately; others will require, in concert with key stakeholders, the ability to first translate a complex commercial need into a well-defined problem.
Work in an Agile way to orchestrate cross-functional projects for designing and testing new algorithms and models.
Collaborate with marketers, other data scientists and analysts, engineers and software developers to build scalable solutions as needed.
About you
You should be qualified to at least a degree level (ideally Masters or PhD) in a quantitative field such as computer science, physics, mathematics, statistics or machine learning.
You should have strong experience in the areas of data mining, machine learning, optimisation and simulation and should be an expert in analysing large, complex, multi-dimensional datasets with a variety of tools.
You should have good knowledge of at least one programming language relevant to data science, i.e. Python, R, Java, Scala, etc. and the associated libraries.
Experience with a variety of predictive algorithms is highly desirable, e.g. Bayesian models, random forests, SVMs, neural nets, etc., as well as an understanding of their theoretical properties and the circumstances under which they are appropriate or not.
In addition, you will have experience deriving data-driven business insights in a commercial environment and be a clear communicator with a highly collaborative approach and the ability to adapt and learn quickly in a rapidly changing environment.
If this sounds like you and you’d like to be a part of a fast paced, growing business with the vision to become the most influential company and best-loved brand in life sciences please apply now!
About Us
Ever since 1998, when our founder, Jonathan Milner, started selling antibodies from the back of his bike, Abcam has aimed to help scientific researchers make breakthroughs faster. We now have offices and labs in the UK, the US, China and Japan, and as we continue to grow, we remain ambitious, driven by our customers’ success and their research needs.
It’s our goal to provide a world-standard in protein research tools, technical support and delivery. When you join Abcam, you’ll join a global business with the passion and the vision to become the most influential company, and, best-loved brand in life sciences.
Our culture is our key differentiator. We believe in empowering individuals, with responsibility given at an early stage. The working environment is fun and fast-paced, collaborative and outcome focused, with a strong customer focus. In addition to competitive salaries, we offer an attractive and flexible benefits package (which includes shares for eligible employees), a culture focussed on wellbeing and opportunities for growth and development.
22/10/2018
Full time
About the role
This will sit within our established Consumer Insights and Analytics team and will help build marketing capability and improve product development with machine learning techniques. The role encompasses orchestrating how the company uses both internal and external large/semi-structured/unstructured data to predict future R&D opportunities as well as real-time algorithms to deliver personalised marketing and web experiences.
About Consumer Insights & Analytics at Abcam
The goal of the Consumer Insights and Analytics team is to catalyse growth across Abcam by helping the organization to transform consumer data into products and initiatives that help life scientists achieve their mission, faster.We are a team of market research, market intelligence, data analyst and data scientist specialists who enjoy working together and in our specialist areas to solve novel and knotty questions for the organisation. We are a growing team with lots of opportunities to influence the business and extend and utilize your skills across a wide range of areas.
Roles & responsibilities:
Encourage the use of data science and data-driven decision-making in the larger organisation.
Innovate and implement machine learning algorithms that discover actionable patterns or inform hypotheses and insights.
Clean and link complex datasets.
Innovate and provide solutions for the business. Some of the problems encountered may be solved immediately; others will require, in concert with key stakeholders, the ability to first translate a complex commercial need into a well-defined problem.
Work in an Agile way to orchestrate cross-functional projects for designing and testing new algorithms and models.
Collaborate with marketers, other data scientists and analysts, engineers and software developers to build scalable solutions as needed.
About you
You should be qualified to at least a degree level (ideally Masters or PhD) in a quantitative field such as computer science, physics, mathematics, statistics or machine learning.
You should have strong experience in the areas of data mining, machine learning, optimisation and simulation and should be an expert in analysing large, complex, multi-dimensional datasets with a variety of tools.
You should have good knowledge of at least one programming language relevant to data science, i.e. Python, R, Java, Scala, etc. and the associated libraries.
Experience with a variety of predictive algorithms is highly desirable, e.g. Bayesian models, random forests, SVMs, neural nets, etc., as well as an understanding of their theoretical properties and the circumstances under which they are appropriate or not.
In addition, you will have experience deriving data-driven business insights in a commercial environment and be a clear communicator with a highly collaborative approach and the ability to adapt and learn quickly in a rapidly changing environment.
If this sounds like you and you’d like to be a part of a fast paced, growing business with the vision to become the most influential company and best-loved brand in life sciences please apply now!
About Us
Ever since 1998, when our founder, Jonathan Milner, started selling antibodies from the back of his bike, Abcam has aimed to help scientific researchers make breakthroughs faster. We now have offices and labs in the UK, the US, China and Japan, and as we continue to grow, we remain ambitious, driven by our customers’ success and their research needs.
It’s our goal to provide a world-standard in protein research tools, technical support and delivery. When you join Abcam, you’ll join a global business with the passion and the vision to become the most influential company, and, best-loved brand in life sciences.
Our culture is our key differentiator. We believe in empowering individuals, with responsibility given at an early stage. The working environment is fun and fast-paced, collaborative and outcome focused, with a strong customer focus. In addition to competitive salaries, we offer an attractive and flexible benefits package (which includes shares for eligible employees), a culture focussed on wellbeing and opportunities for growth and development.
About the role
This role sits within our established Consumer Insight and Analytics team and will help build marketing capability and improve product development with machine learning techniques. The role encompasses orchestrating how the company uses both internal and external large/semi-structured/unstructured data to predict future R&D opportunities as well as real-time algorithms to deliver personalised marketing and web experiences.
About Consumer Insight & Analytics at Abcam
The goal of the Consumer Insight and Analytics team is to catalyse growth across Abcam by helping the organization to transform data into products and initiatives that help life scientists achieve their mission, faster.
We are a team of market research, market intelligence, data analyst and data scientist specialists who enjoy working together and in our specialist areas to solve novel and knotty questions for the organisation. We are a growing team with lots of opportunities to influence the business and extend and utilize your skills across a wide range of areas.
Roles & responsibilities:
Encourage the use of data science and data-driven decision-making in the larger organisation.
Innovate and implement machine learning algorithms that discover actionable patterns or inform hypotheses and insights.
Clean and link complex datasets.
Innovate and provide solutions for the business. Some of the problems encountered may be solved immediately; others will require, in concert with key stakeholders, the ability to first translate a complex commercial need into a well-defined problem.
Work in an Agile way to orchestrate cross-functional projects for designing and testing new algorithms and models.
Collaborate with marketers, other data scientists and analysts, engineers and software developers to build scalable solutions as needed.
About you
You should be qualified to at least a degree level (ideally Masters or PhD) in a quantitative field such as computer science, physics, mathematics, statistics or machine learning.
You should have strong experience in the areas of data mining, machine learning, optimisation and simulation and should be an expert in analysing large, complex, multi-dimensional datasets with a variety of tools.
You should have good knowledge of at least one programming language relevant to data science, i.e. Python, R, Java, Scala, etc. and the associated libraries.
Experience with a variety of predictive algorithms is highly desirable, e.g. Bayesian models, random forests, SVMs, neural nets, etc., as well as an understanding of their theoretical properties and the circumstances under which they are appropriate or not.
In addition, you should be a clear communicator with a highly collaborative approach and the ability to adapt and learn quickly in a rapidly changing environment.
If this sounds like you and you’d like to be a part of a fast paced, growing business with the vision to become the most influential company and best-loved brand in life sciences please apply now!
About Us
Ever since 1998, when our founder, Jonathan Milner, started selling antibodies from the back of his bike, Abcam has aimed to help scientific researchers make breakthroughs faster. We now have offices and labs in the UK, the US, China and Japan, and as we continue to grow, we remain ambitious, driven by our customers’ success and their research needs.
It’s our goal to provide a world-standard in protein research tools, technical support and delivery. When you join Abcam, you’ll join a global business with the passion and the vision to become the most influential company, and, best-loved brand in life sciences.
Our culture is our key differentiator. We believe in empowering individuals, with responsibility given at an early stage. The working environment is fun and fast-paced, collaborative and outcome focused, with a strong customer focus. In addition to competitive salaries, we offer an attractive and flexible benefits package (which includes shares for eligible employees), a culture focussed on wellbeing and opportunities for growth
22/10/2018
Full time
About the role
This role sits within our established Consumer Insight and Analytics team and will help build marketing capability and improve product development with machine learning techniques. The role encompasses orchestrating how the company uses both internal and external large/semi-structured/unstructured data to predict future R&D opportunities as well as real-time algorithms to deliver personalised marketing and web experiences.
About Consumer Insight & Analytics at Abcam
The goal of the Consumer Insight and Analytics team is to catalyse growth across Abcam by helping the organization to transform data into products and initiatives that help life scientists achieve their mission, faster.
We are a team of market research, market intelligence, data analyst and data scientist specialists who enjoy working together and in our specialist areas to solve novel and knotty questions for the organisation. We are a growing team with lots of opportunities to influence the business and extend and utilize your skills across a wide range of areas.
Roles & responsibilities:
Encourage the use of data science and data-driven decision-making in the larger organisation.
Innovate and implement machine learning algorithms that discover actionable patterns or inform hypotheses and insights.
Clean and link complex datasets.
Innovate and provide solutions for the business. Some of the problems encountered may be solved immediately; others will require, in concert with key stakeholders, the ability to first translate a complex commercial need into a well-defined problem.
Work in an Agile way to orchestrate cross-functional projects for designing and testing new algorithms and models.
Collaborate with marketers, other data scientists and analysts, engineers and software developers to build scalable solutions as needed.
About you
You should be qualified to at least a degree level (ideally Masters or PhD) in a quantitative field such as computer science, physics, mathematics, statistics or machine learning.
You should have strong experience in the areas of data mining, machine learning, optimisation and simulation and should be an expert in analysing large, complex, multi-dimensional datasets with a variety of tools.
You should have good knowledge of at least one programming language relevant to data science, i.e. Python, R, Java, Scala, etc. and the associated libraries.
Experience with a variety of predictive algorithms is highly desirable, e.g. Bayesian models, random forests, SVMs, neural nets, etc., as well as an understanding of their theoretical properties and the circumstances under which they are appropriate or not.
In addition, you should be a clear communicator with a highly collaborative approach and the ability to adapt and learn quickly in a rapidly changing environment.
If this sounds like you and you’d like to be a part of a fast paced, growing business with the vision to become the most influential company and best-loved brand in life sciences please apply now!
About Us
Ever since 1998, when our founder, Jonathan Milner, started selling antibodies from the back of his bike, Abcam has aimed to help scientific researchers make breakthroughs faster. We now have offices and labs in the UK, the US, China and Japan, and as we continue to grow, we remain ambitious, driven by our customers’ success and their research needs.
It’s our goal to provide a world-standard in protein research tools, technical support and delivery. When you join Abcam, you’ll join a global business with the passion and the vision to become the most influential company, and, best-loved brand in life sciences.
Our culture is our key differentiator. We believe in empowering individuals, with responsibility given at an early stage. The working environment is fun and fast-paced, collaborative and outcome focused, with a strong customer focus. In addition to competitive salaries, we offer an attractive and flexible benefits package (which includes shares for eligible employees), a culture focussed on wellbeing and opportunities for growth
About the role:
Abcam is looking for a Data Engineer who will design, construct and maintain the data architectures used by the Consumer Insight and Analytics team. The role encompasses the streamlining of existing data pipelines as well as the creation of new ones. The data in question is both structured and unstructured and relates to both customer interactions and product development. At present Abcam does not implement a distributed data storage and processing paradigm and thus experience with one is not essential. That said, in the future this will likely change and the ability to guide the company along this journey would be a decided bonus.
Roles & responsibilities:
Automating the provision of clean, structured and consistent data to tools produced by data scientists and data analysts.
Automating the extraction of data from a variety of tools and platforms.
Recommending ways to improve data reliability and quality.
About you:
You will be degree qualified in a rigorous quantitative field (e.g. computer science, mathematics, physics etc), a computer science degree would be advantageous, but not essential.
You will be a highly collaborative self-starter with expertise in SQL and experience in writing production code and creating data pipelines.
You will have familiarity with Python and the commonly-used data science libraries (i.e. pandas and scikit-learn).
In addition, you will be familiar with Linux and shell scripting with the ability to establish and maintain a relational database.
You will have excellent prioritisation and project management skills with the ability to adapt and learn quickly in a changing environment. Familiarity with at least some part of the Hadoop ecosystem and with Oracle products would be beneficial. If this sounds like you and you’d like to be a part of a fast paced, growing business with the vision to become the most influential company and best-loved brand in life sciences please apply now!
About Us
Ever since 1998, when our founder, Jonathan Milner, started selling antibodies from the back of his bike, Abcam has aimed to help scientific researchers make breakthroughs faster. We now have offices and labs in the UK, the US, China and Japan, and as we continue to grow, we remain ambitious, driven by our customers’ success and their research needs.
It’s our goal to provide a world-standard in protein research tools, technical support and delivery. When you join Abcam, you’ll join a global business with the passion and the vision to become the most influential company, and, best-loved brand in life sciences.
Our culture is our key differentiator. We believe in empowering individuals, with responsibility given at an early stage. The working environment is fun and fast-paced, collaborative and outcome focused, with a strong customer focus. In addition to competitive salaries, we offer an attractive and flexible benefits package (which includes shares for eligible employees), a culture focussed on wellbeing and opportunities for growth.
22/10/2018
Full time
About the role:
Abcam is looking for a Data Engineer who will design, construct and maintain the data architectures used by the Consumer Insight and Analytics team. The role encompasses the streamlining of existing data pipelines as well as the creation of new ones. The data in question is both structured and unstructured and relates to both customer interactions and product development. At present Abcam does not implement a distributed data storage and processing paradigm and thus experience with one is not essential. That said, in the future this will likely change and the ability to guide the company along this journey would be a decided bonus.
Roles & responsibilities:
Automating the provision of clean, structured and consistent data to tools produced by data scientists and data analysts.
Automating the extraction of data from a variety of tools and platforms.
Recommending ways to improve data reliability and quality.
About you:
You will be degree qualified in a rigorous quantitative field (e.g. computer science, mathematics, physics etc), a computer science degree would be advantageous, but not essential.
You will be a highly collaborative self-starter with expertise in SQL and experience in writing production code and creating data pipelines.
You will have familiarity with Python and the commonly-used data science libraries (i.e. pandas and scikit-learn).
In addition, you will be familiar with Linux and shell scripting with the ability to establish and maintain a relational database.
You will have excellent prioritisation and project management skills with the ability to adapt and learn quickly in a changing environment. Familiarity with at least some part of the Hadoop ecosystem and with Oracle products would be beneficial. If this sounds like you and you’d like to be a part of a fast paced, growing business with the vision to become the most influential company and best-loved brand in life sciences please apply now!
About Us
Ever since 1998, when our founder, Jonathan Milner, started selling antibodies from the back of his bike, Abcam has aimed to help scientific researchers make breakthroughs faster. We now have offices and labs in the UK, the US, China and Japan, and as we continue to grow, we remain ambitious, driven by our customers’ success and their research needs.
It’s our goal to provide a world-standard in protein research tools, technical support and delivery. When you join Abcam, you’ll join a global business with the passion and the vision to become the most influential company, and, best-loved brand in life sciences.
Our culture is our key differentiator. We believe in empowering individuals, with responsibility given at an early stage. The working environment is fun and fast-paced, collaborative and outcome focused, with a strong customer focus. In addition to competitive salaries, we offer an attractive and flexible benefits package (which includes shares for eligible employees), a culture focussed on wellbeing and opportunities for growth.
At AstraZeneca we win through science, it’s at the heart of our every success. That science is only possible when we all work together – we’ll always make sure you’re clear about how your role is connected to our wider mission to really show what science can do.
At AstraZeneca we’re relentlessly curious about science, and pursue our work with passion. We believe that when we follow the science we can make game-changing discoveries that can transform the lives of patients around the world.
Summary:
The Real World Evidence Centre of Excellence is a new group being growing within AstraZeneca. AstraZeneca has a pedigree of experience in Real World Evidence, having developed a coherent strategy to develop and internalize rich data assets the group is now amplifying those investments through a Real World Evidence Data Science capability. Data Scientists that are successful in this role will become part of a growing RWE CoE within the Global Medical Affairs organisation, working on challenging problems Data Science can solve for accelerating evidence generation through to insights that could enable AstraZeneca to develop innovative medicines.
He/she will be assist the due diligence on new data providers/vendors to advance AZ’s Real World Evidence (RWE) data maturity, help shape the right analytics strategy for a range of Therapeutic Areas and provide informatics support for data acquisitions.
The ideal candidate for this role will bring a proven track record of delivering value through the leverage of routinely collected data from healthcare settings to provide health analytics and insights in both Public Health, Pharmaceutical Research and Development and Commercial context.
The role provides coaching, task management and support to Programmers/Statistics/Information Scientists, promoting best practice across multiple domains, and/or stakeholder groups.
Typical Accountabilities:
Provide scientific guidance on the application of Real World Evidence and observational research data to support pharmaceutical development problems
Support Pharmacovigilance teams and Epidemiologists extract value from large observational research data
Support technical teams provide access to analytical tools and develop visual analytics to enable self-serving applications for end customers
Provide clear technical input, options, and direction to strategic decisions on RWE platform and capability build
Provide strategic decisions on AZ Medical Evidence and Observational Research external collaborations in the US and other markets
Provide technical input, options and directions to strategic decisions made by AZ observational study teams on study design, data partner selection and best practices in RWE data utilization
Assist in building a capability that becomes a source of sustained competitive advantage for AZ/MedImmune in identifying, acquiring, integrating and mining diverse RWE data from multiple geographic and healthcare system sources to support evidence generation and real-world studies
Assist in the delivery of analytics and the build of analytics pieces as part of an RWE strategy
Evaluate and assess strengths and weaknesses of external RWE data sources via interrogation, and potential partners for advancing the data strategy for a given therapeutic area
Maintain a strong insight into the capabilities of potential external partners in RWE, especially for US and emerging markets.
Education, Qualifications, Skills and Experience
Essential:
PhD in data science or other advanced degree in life sciences with post doctoral or other training/work in Medical Informatics or related field
Expertise in EMR/Health IT, disease registries, and insurance claims databases
Expertise in clinical data standards, medical terminologies and controlled vocabularies used in healthcare data and ontologies (ICD9/10/ReadCode)
Experience in Statistical Analysis Plan (SAP) generation and execution for observational studies
Expertise in data mining approaches within healthcare settings generating insight from routinely collected healthcare data
Expertise in methods development and application using statistical languages such as R/Matlab/SAS/SQL/Hadoop/Python
Experience in advanced visualisation and visual analytics of routinely collected healthcare data
Experience in real-world evidence and familiarity with health economics/epidemiology, and quantitative science such as health outcome modelling
Strong track record in delivering leading edge informatics solutions in pharmaceutical R&D and commercial environments
Desirable:
Experience in supporting pharmacoepidemiology studies with proven track record of advancing approaches with data science
A history of patient care or equivalent background of working at a patient care setting that allows the candidate to bring medical perspective into real-world evidence generation and observational studies
Demonstrated ability to build long-term relationships with stakeholders at senior levels, understand relevant scientific/business challenges at a deep level and translate into a programme of informatics activities to deliver defined value
Ability to lead & manage multi-disciplinary health informatics projects
Strong track record of delivering large, cross functional projects
Experience working in a global organization and delivering global solutions
Key Relationships to reach solutions
Internal (To AZ or teams)
Observational Research teams
Global Medical Affairs Leads
Payer Evidence & Planning
Product and portfolio strategy
Global Medicines Development
Medical Evidence Planning
Key experts in Informatics/Analytics environments at AZ/MedImmune, and external partner organizations.
External
AZ RWE existing, prospective or potential partner organizations,
Key academic collaborators and thought leaders
AstraZeneca is an equal opportunity employer. AstraZeneca will consider all qualified applicants for employment without discrimination on grounds of disability, gender or gender orientation, pregnancy or maternity leave status, race or national or ethnic origin, age, religion or belief, gender identity or re-assignment, marital or civil partnership status, protected veteran status (if applicable) or any other characteristic protected by law.
22/10/2018
Full time
At AstraZeneca we win through science, it’s at the heart of our every success. That science is only possible when we all work together – we’ll always make sure you’re clear about how your role is connected to our wider mission to really show what science can do.
At AstraZeneca we’re relentlessly curious about science, and pursue our work with passion. We believe that when we follow the science we can make game-changing discoveries that can transform the lives of patients around the world.
Summary:
The Real World Evidence Centre of Excellence is a new group being growing within AstraZeneca. AstraZeneca has a pedigree of experience in Real World Evidence, having developed a coherent strategy to develop and internalize rich data assets the group is now amplifying those investments through a Real World Evidence Data Science capability. Data Scientists that are successful in this role will become part of a growing RWE CoE within the Global Medical Affairs organisation, working on challenging problems Data Science can solve for accelerating evidence generation through to insights that could enable AstraZeneca to develop innovative medicines.
He/she will be assist the due diligence on new data providers/vendors to advance AZ’s Real World Evidence (RWE) data maturity, help shape the right analytics strategy for a range of Therapeutic Areas and provide informatics support for data acquisitions.
The ideal candidate for this role will bring a proven track record of delivering value through the leverage of routinely collected data from healthcare settings to provide health analytics and insights in both Public Health, Pharmaceutical Research and Development and Commercial context.
The role provides coaching, task management and support to Programmers/Statistics/Information Scientists, promoting best practice across multiple domains, and/or stakeholder groups.
Typical Accountabilities:
Provide scientific guidance on the application of Real World Evidence and observational research data to support pharmaceutical development problems
Support Pharmacovigilance teams and Epidemiologists extract value from large observational research data
Support technical teams provide access to analytical tools and develop visual analytics to enable self-serving applications for end customers
Provide clear technical input, options, and direction to strategic decisions on RWE platform and capability build
Provide strategic decisions on AZ Medical Evidence and Observational Research external collaborations in the US and other markets
Provide technical input, options and directions to strategic decisions made by AZ observational study teams on study design, data partner selection and best practices in RWE data utilization
Assist in building a capability that becomes a source of sustained competitive advantage for AZ/MedImmune in identifying, acquiring, integrating and mining diverse RWE data from multiple geographic and healthcare system sources to support evidence generation and real-world studies
Assist in the delivery of analytics and the build of analytics pieces as part of an RWE strategy
Evaluate and assess strengths and weaknesses of external RWE data sources via interrogation, and potential partners for advancing the data strategy for a given therapeutic area
Maintain a strong insight into the capabilities of potential external partners in RWE, especially for US and emerging markets.
Education, Qualifications, Skills and Experience
Essential:
PhD in data science or other advanced degree in life sciences with post doctoral or other training/work in Medical Informatics or related field
Expertise in EMR/Health IT, disease registries, and insurance claims databases
Expertise in clinical data standards, medical terminologies and controlled vocabularies used in healthcare data and ontologies (ICD9/10/ReadCode)
Experience in Statistical Analysis Plan (SAP) generation and execution for observational studies
Expertise in data mining approaches within healthcare settings generating insight from routinely collected healthcare data
Expertise in methods development and application using statistical languages such as R/Matlab/SAS/SQL/Hadoop/Python
Experience in advanced visualisation and visual analytics of routinely collected healthcare data
Experience in real-world evidence and familiarity with health economics/epidemiology, and quantitative science such as health outcome modelling
Strong track record in delivering leading edge informatics solutions in pharmaceutical R&D and commercial environments
Desirable:
Experience in supporting pharmacoepidemiology studies with proven track record of advancing approaches with data science
A history of patient care or equivalent background of working at a patient care setting that allows the candidate to bring medical perspective into real-world evidence generation and observational studies
Demonstrated ability to build long-term relationships with stakeholders at senior levels, understand relevant scientific/business challenges at a deep level and translate into a programme of informatics activities to deliver defined value
Ability to lead & manage multi-disciplinary health informatics projects
Strong track record of delivering large, cross functional projects
Experience working in a global organization and delivering global solutions
Key Relationships to reach solutions
Internal (To AZ or teams)
Observational Research teams
Global Medical Affairs Leads
Payer Evidence & Planning
Product and portfolio strategy
Global Medicines Development
Medical Evidence Planning
Key experts in Informatics/Analytics environments at AZ/MedImmune, and external partner organizations.
External
AZ RWE existing, prospective or potential partner organizations,
Key academic collaborators and thought leaders
AstraZeneca is an equal opportunity employer. AstraZeneca will consider all qualified applicants for employment without discrimination on grounds of disability, gender or gender orientation, pregnancy or maternity leave status, race or national or ethnic origin, age, religion or belief, gender identity or re-assignment, marital or civil partnership status, protected veteran status (if applicable) or any other characteristic protected by law.
