Trainee Data Science Engineer

  • Royal London Group
  • Edinburgh, UK
  • 15/01/2022
Full time Data Science Data Analytics Data Management Biostatistics

Job Description

Job title: Trainee Data Science Engineer
Contract type: Permanent
Closing date: 24th January 2022
Location: Edinburgh

Royal London is the largest mutual life insurance, pensions and investment company in the UK. Since its foundation 160 years ago, Royal London has supported millions of people to protect and provide for themselves and their families.
Our culture is welcoming, friendly, flexible and we aim to make you always feel included. We welcome applications from individuals who have taken an extended career break or those who are transitioning from different sectors.
To support this we are always open to discussing flexible working arrangements and as we transition to hybrid working we will discuss working patterns or locations that ensure you have the freedom to be your best. It’s what makes Royal London a great place to work.
We believe that being together some of the time will help our colleagues to feel truly connected to our Spirit of Royal London culture. Many of us value the passing conversations, social interactions and building relationships that comes from being together in the office.
We currently have an exciting opportunity to bring onboard a Trainee Data Science Engineer to join Royal London’s newly created Data Office and support the Data Analytics team on permanent contract in Edinburgh.

Role purpose

In this role, you will join the Data Analytics team to contribute to the delivery of analytics, data science, and Machine Learning projects to create insights, answer key business questions, solve business problems, and support decision making at all levels of the organisation. You will have exposure to all three areas of Data Science, Data Visualisation and Data Engineering.

Key Responsibilities

Contribute to the development of Machine Learning and Artificial Intelligence applications, algorithms, models, and other analytics solutions.
Build appropriate data assets to support analysis.
Prototype solutions to explore business hypothesis in an agile and iterative way which supports a learn fast/fail fast methodology.
Communicate findings and results of these initiatives back to the business, stakeholders, and subject matter experts.
Engage with others and maintain effective relationships with immediate team members, peers, and immediate customers.
Work with more senior team members to distil insights and findings into clear stories that are relevant to the business.
Visualise and share insight in readily consumable formats for a non-technical audience.

Essential Criteria

Interest and enthusiasm for a career in data engineering and data science
Ability to collaborate across teams
Enthusiasm to learn and develop skills

Desirable Criteria

Knowledge and understanding of Python, Data Bricks and SQL
Degree level qualification or equivalent in mathematics, statistics, economics, engineering, physics, Computer Science or related discipline such as Data Science or Big Data.

What we offer

We've always been proud to reward employees by offering a number of benefits such as Pensions and Protection, Performance and role-related benefits, Lifestyle and Wellbeing
Our culture comes from within, or to put it another way, it comes from our people. It’s what makes Royal London a great place to work.
Our People Promise is something we live up to every day. We know we can rely on you, and you can expect plenty from us in return.
Glassdoor have again ranked as among the best places to work in the UK
We are an equal opportunities employer. We work hard to attract the best talent for our award-winning team. We believe that embracing difference makes us stronger. Our diverse people bring us different skills – whatever their educational background, disability, gender, age, sexual orientation, race, religion or belief.
In fact, the first pillar of our People Promise is designed to make sure you 'work somewhere inclusive'. We want to live up to this promise; it’s good for our people and good for our customers too, because our workforce should reflect our communities.