Job Description
Our client, a leading global IT consulting company, is recruiting for a NRM/TIM Senior Data Scientistto join their business in theUnited Kingdom.
Job Description:
1. An experienced Data Scientist required to develop and support the roll out of a new global TIM programme. The Trade Investment Management (TIM) is a top priority strategic initiative, it is aimed at sales planning and optimisation to drive growth across our business. At the heart of TIM is a bespoke counterfactual model and promotion optimisation which analyze the effectiveness of promotional campaigns in order to devise optimal marketing objectives and strategies.
2. The CH Data Science Team is currently developing and scaling the programme to new markets. You will be working with our Principal Data Scientist alongside with the TIM Squad (consists of Data Scientists, ML Engineer and Data Engineer).
Responsibilities:
3. Work with existing teams to develop, optimize and deploy counterfactual and promotion optimization models.
4. Develop high quality and robust code.
5. Assist in the improvement and scalability enhancement tasks on the code base.
6. Mentor and upskill more junior members of the team.
Requirements:
7. MSc or higher degree in STEM subject.
8. Proven experience in building and deploying machine learning models.
9. Experience in conceptualizing, formulating, prototype and implementing algorithms to solve business problems.
10. At least 7 years of OOP development using Python, with excellent and broad knowledge of popular Python packages, e.g. statsmodels, sktime, lightgbm etc
11. Strong experience in the complete SDLC process.
12. Experienced in Agile methodologies and hypothesis-driven approach.
Nice to have:
13. Experience with cloud platforms, particularly Azure and optimisation libraries such as Gurobi.
14. Experience in software engineering concepts such as robust programming, graceful exit.
15. Experience of software development and deployment lifecycle, especially CICD pipelines and version control e.g. git.
16. Have an in-depth understanding of statistical modeling techniques and the mathematical foundations of applied ML algorithms and models.