Job description Posted 14 September 2021

Senior Data Scientist

Remote / Brentford (1 day a week in office)

Until end of year with view to extend

Up to £655 per day via umbrella


Senior Data scientist required to work with the Data Science team to support on TIM initiatives.


We have several initiatives around sales, consumption and promotions. We need additional resource to help with models’ developments, forecasting algorithms, intervention analysis and simulations. The overall goal of these projects is to utilise the data captured by us and our partners to augment the Comex team?ability to?understand the effect of promotional activities and cannibalization on orders, consumption and revenue.



Requirements:

• Proven extensive experience developing and implementing Machine Learning algorithms on large data sets

• Be an expert in Python and R programming for Data Science and Time Series analysis

• Have in depth understanding of statistical modelling / ML techniques for time series forecasting (ARIMA, ETS, Prophet, Time Series pattern detection, and ML methods)

• Strong experience with Causal inference, Intervention analysis, Counterfactuals Estimation and Scenarios simulation

• Solid experience with Probabilistic Programming and Bayesian Methods

• Be an expert in Python programming for Data Science (pandas, numpy, sklearn, statsmodels)

• Be an expert in mining large & very complex data sets using SQL and Spark

• Have in depth understanding of statistical modelling techniques and the mathematical foundations of applied ML and AI algorithms and models

• Have a good working knowledge cloud-based data science frameworks and toolkits. Working knowledge of Azure is preferred

• Strong experience in ML lifecycle management. Working knowledge of mlflow is preferred

• Are experienced in Agile methodologies and the hypothesis-driven approach

• Have a deep knowledge of a sufficiently broad area of technical specialism (e.g. Machine Learning, Optimisation, Applied Mathematics, Simulation, Bayesian Methods etc.), and are a valued and trusted expert

Responsibilities:

• Contribute to all aspects of the Data Science Project Lifecycle from scope through to production

• Provide leadership and guidance on monitoring ongoing data quality and model performance

• Own and define the key performance indicators (KPIs) and diagnostics to measure performance against business goals

• Compile, integrate, and analyse data from multiple sources to answer business questions

• Conceptualize, formulate, prototype and implement algorithms to solve business problems