Apply the data science product lifecycle principles to new projects (Design, exploratory data analysis, building, evaluation, deployment, monitoring and maintenance)
Contribute to developing production data science models, monitoring their performance, and managing their lifecycle (retraining, optimising and upgrading)
Work on the end to end data solution including understanding complex business challenges, designing scientific solutions, working large and small data sets (including 3rd party and internal data of a wide variety), using cutting-edge machine learning or statistical modelling techniques to derive insights
Work collaboratively with data scientists, data engineers and other technical people including pricing teams in order to help support maturation of analytics practice within the organization.
Write high quality python code using industry best practice for model training and deployment
Continuous development of knowledge base and experience, including researching new techniques and technologies, communicating this back with the team

Experience of data science, advanced analytics or a genuine interest to learn.
Ability to conduct high quality research in a suitably timely manner working in both independently and in small teams as required by the task.
Familiarity with version control and other IT delivery tools is required
Understanding / identifying opportunity to apply machine learning knowledge to solve business problems
Experience in developing predictive and prescriptive analysis (predictive modelling, machine learning or data mining) used to draw key business insights and clearly articulate findings for target audience
Exceptional written communications skills and effective presentation skills
Willingness to learn best practice in software development
Strong python programming skills
Experience of TDD (pytest or other testing framework)

Data Scientist

Key skills