Data Scientist Job In London

In-office requirement: 4-days per week in office in city centre, London.

Our client is looking for a Data Scientist to work on the betting and prediction side of their business, helping them to improve our ability to predict match outcomes. This role involves researching ways in which the modelling approaches they use to predict football matches can be improved, and then turning those insights into practical modelling solutions that they can deploy to production.

Requirements

• Strong problem solving skills, with an ability to proactively identify challenges and propose solutions;
• Interest in football and betting/prediction problems;
• An ability to make pragmatic and sensible choices about what data analysis and modelling approaches to use – you can judge when it’s right to obsess about the details, and when it’s right to ship an MVP as fast as possible;
• A flair for communicating statistical analyses to both technical and non-technical audiences;
• Experience with statistical analysis and predictive modelling - you don’t need to be an expert in any one area, but you need to know what techniques and tools are available, and understand the trade-offs of using different approaches;
• Experience with SQL and relational databases – you can quickly understand a new dataset, perform exploratory analysis, identify data quality issues, and take pragmatic decisions about how to handle imperfect data;
• Some programming experience, preferably with Python.

For senior candidates

More experienced candidates will have the opportunity to take on more responsibility, leading projects and helping set the direction of our research. We are looking for candidates who can think strategically and make pragmatic decisions about where we should focus our efforts, and what technical approaches we should use to get our modelling ideas onto production. In addition to the requirements above, this means you also have:

• 3+ years of practical data science experience;
• Project management skills, including an ability to make sensible value judgements about where the team should spend time;
• An extensive knowledge of statistical methods and machine learning techniques;
• Strong programming skills, ideally with Python;
• Experience working with other data scientists on a collaborative codebase;
• Experience of deploying models to production, ideally in AWS or another cloud environment.