Data Scientist

  • Wood Mackenzie
  • Edinburgh, UK
  • 01/12/2021
Full time Data Science Machine Learning Business Intelligence Data Management

Job Description

Company Description
Wood Mackenzie is the global leader in data, analysis and consulting across the energy, chemicals, metals, mining, power and renewables sectors.

Founded in 1973, our success has always been underpinned by the simple principle of providing trusted research and advice that makes a difference to our customers. Today we have over 2,000 customers ranging from the largest global energy companies and financial institutions to governments as well as smaller market specialists.

Our teams are located around the world. This enables us to stay closely connected with customers and the markets and sectors we cover. Collectively this allows us to offer a compelling combination of global commodity analysis with detailed local market knowledge.

We are committed to supporting our people to grow and thrive. We value different perspectives and aspire to create an inclusive environment that encourages diversity and fosters a sense of belonging. We are committed to creating a workplace that works for you and encourage everyone to get involved in our Wellness, Diversity and Inclusion, and Community Engagement initiatives. We actively support flexible working and are happy to consider alternative work patterns, taking into account your needs and the needs of the team or division that you are looking to join.

Hear what our team has to say about working with us:

https://www.woodmac.com/careers/our-people/
Job Description
The Data Scientist will collaborate closely with the marketing team and other business stakeholders, analysing and interpreting internal customer and marketing data our broad set of platforms and systems to deliver customer and marketing performance insight and make recommendations for performance improvement.

Main Responsibilities

  • Build algorithms and design experiments to merge, manage, interrogate, and extract data to supply tailored reports to marketing colleagues or wider organisations.
  • Use machine learning tools and statistical techniques to produce solutions to problems.
  • Test data mining models to select the most appropriate ones for a project, such as segmentation, attribution modeling, white space mapping, etc.
  • Maintain clear and coherent communication, both verbal and written, to understand data needs and report results.
  • Create clear reports that tell compelling stories about how marketing and the wider business performs.
  • Assess the effectiveness of data sources and data-gathering techniques and improve data collection methods.
  • Horizon scan to stay up to date with the latest technology, techniques, and methods.
  • Look for opportunities to use insights/datasets/code/models across other functions in the organisation (for example, in the HR and Sales departments).
  • Stay curious and enthusiastic about using algorithms to solve problems and enthuse others to see the benefit of your work.

Qualifications
Experience, Knowledge & Behaviours

  • Excellent understanding of machine learning techniques and algorithms.
  • Experience with common data science toolkits, such as R, Weka, NumPy, MatLab, etc. Excellence in at least one of these is highly desirable.
  • Great communication skills.
  • Experience with data visualisation tools, such as Powerbi, Tableau, etc.
  • Proficiency in using query languages such as SQL, Python, Hive, Pig.
  • Experience with working across large databases.
  • Good applied statistics skills, such as distributions, statistical testing, regression, etc.
  • Good scripting and programming skills.
  • Data-oriented personality.
  • Performs well managing multiple priorities and working in a matrixed environment.
  • Team player and happy to voice an opinion.
  • Self-motivated, professional, and proactive.
  • Comfortable delivering to tight deadlines.
  • Able to build and maintain effective relationships.

Strong customer focus, both internal and external
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Additional Information
Verisk Analytics is an equal opportunity employer.

All members of the Verisk Analytics family of companies are equal opportunity employers. We consider all qualified applicants for employment without regard to race, religion, color, national origin, citizenship, sex, gender identity and/or expression, sexual orientation, veteran's status, age or disability.

http://www.verisk.com/careers.html

Unsolicited resumes sent to Verisk, including unsolicited resumes sent to a Verisk business mailing address, fax machine or email address, or directly to Verisk employees, will be considered Verisk property. Verisk will NOT pay a fee for any placement resulting from the receipt of an unsolicited resume.