Senior Data Scientist
GlaxoSmithKline
- Brentford, Greater London London
- Permanent
- Full-time
- Translate a business need into a well-defined machine learning problem and execute on that solution in an interdisciplinary team. The Senior Data Scientist will be able to actively identify opportunities to apply machine learning to build, test, and validate predictive models. They should be the standard bearer for good coding practices and promote proper unit, functional, and integration tests for code to ensure quality.
- Able to explore and evaluate the appropriateness of the data for the intended task. The Senior Data Scientist will be experienced in designing models that perform to a particular specification and be able to evaluate the model that will best suit the problem at hand.
- Compare results from various methodologies and recommend the best techniques to stake holders and able to defend robustly in meetings with senior leaders.
- They should be capable of thinking in advance of model's future requirements or how the available data might change over time and design a product that will be able to cope with those requirements.
- Assume leadership of some, or all, of a product ship.
- Be the ‘go to’ person for specific methodologies and mentor junior data scientists on the team and share ideas in an open collegiate way.
- Continually learn new analytical skills, techniques and tools to improve competitive advantage; participate in internal & external technology communities.
- Communicate technical subject matter clearly and concisely to audiences of various backgrounds.
- BSc degree in a STEM-related discipline (Mathematics or Engineering, Data Science/ML, Statistics, Computer Science, Physics) with extensive experience in data science/related, utilising software engineering best practices/technologies
- Extensive experience of designing, developing and implementing analytical solutions using a variety of tools, with deep experience in SQL and Python. Working knowledge and experience with cloud based and local data science frameworks and toolkits.
- Experience of comparing results from various methodologies then explaining the technical concepts at all levels in the organization, including senior managers/stakeholders.
- The ability to extract insight from large, multiparametric data sets , delivered through experience in two or more of these areas is required: Supervised Learning, Probabilistic Inference, Statistical Modelling, Bayesian Statistics, Unsupervised Learning or Reinforcement Learning
- Working knowledge and experience of project management methodologies, include Agile methodologies and the hypothesis-driven approach
- Have a strong desire and commitment to coach and develop other, more junior team members, on best practices in data science.
- Background in Software Engineering
- Experience with NLP tooling, including LLM access via API
- Experience in delivering solutions to production via Continuous Integration/Continuous Delivery.
- Experience with MS Azure stack and/or Databricks
- Experience with Docker
- Knowledge and experience of people data landscape .
- Experience in healthcare or pharmaceutical industries.