Senior Data Scientist: Python Programming, Statistical Modelling
- Brentford, Greater London (GBR)
- £600 - £640 Per Day
- 3 Months
- Start date: ASAP
- Ref: SDSCITBC
- data quality
- spark
- data science
- programming
- python
- prototype
- sql
- cloud
- simulation
- pipeline
- monitoring
- sales
- agile
- time series forecasting
- forecasting
Senior Data Scientist: Python Programming, Statistical Modelling
Role will be initially working from home but based in Brentford thereafter
Job Spec
Senior data scientist required to work with the GSK Data Science team on the Suggested Orders project, developing models for recommender systems and forecasting. The aim of this project is to utilise the data captured by GSK and our partners to augment the sales reps ability to generate orders. The data team will build, test and deploy a Machine Learning Solution that takes input data for sell-in, sell-out and pharmacy stock and generates a suggested order. The model will be productionised as part of the model pipeline. You will be working with our Principal Data Scientist for Sales and Marketing and another Senior Data Scientist.
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
Requirements:
- Proven extensive experience developing and implementing Machine Learning algorithms on large data sets
- 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.
- Experience with at least one Deep Learning framework (e.g. pytorch, tensorflow, keras)
- Have in depth understanding of statistical modelling techniques and the mathematical foundations of applied ML and AI algorithms and models. Particularly time series forecasting and recommender systems methods.
- Have a good working knowledge cloud-based data science frameworks and toolkits. Working knowledge of Azure is preferred.
- Experience building large scale machine learning systems (e.g. orchestration via Airflow)
- 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
