Data Scientist (x4 roles available)
Salary: £40-65k plus attractive bonus on top
Location: London or Leeds (hybrid working an option, if preferred)
*Please only apply if you have an interest in sports betting/analytics, you will be asked questions on this*
Company:
My client is a data driven sports forecasting business specialising in betting odds generation, trading & risk management. They build player-level, play-by-play simulators that produce the most accurate lines in the industry across the major US sports.
Purpose of role:
As a Data Scientist within the Modelling team, you will play an integral part by driving the implementation of our product offering and ensuring the business meets client demands with respect to accurate and low latency sports forecasts.
Key responsibilities:
Extract meaningful insight from sports data using sound Mathematical/Statistical principles.4
Build models and perform ad hoc analysis using a variety of data sources to solve tasks relevant to the business (e.g. supporting development of existing and/or new sports forecasting products).
Collaborate with other members of the Data Science team to propose ideas and solve modelling problems relating to new/existing products.
Follow typical development processes in terms of code management and structure.
Liaise with various teams around the business (including Model Engineering and Data Collection teams where appropriate) to assist with tasks relevant to the modelling team.
Skills and competencies:
Experience solving analytics and modelling problems.
Experience working with Python/R.
Familiarity with data munging and data processing tools (e.g. Numpy, Pandas, dplyr).
Knowledge of statistical modeling and machine learning, with relevant experience in the use of relevant Python libraries e.g. scikit-learn, xgboost, tensorflow, pymc3, statsmodels (and R equivalents).
Familiarity with SQL and experience working with relational databases.
Problem-solving skills with a pragmatic and analytical outlook.
Some knowledge of the sports betting/analytics industry, preferably in sports betting pricing, you don't need to be focused on any specific sport.
Desirable:
Familiar with data engineering and development for machine learning.
Experience working on the .Net framework, preferably with C#.
Familiarity with DevOps.
Knowledge of Kafka or equivalent distributed event store and stream-processing platform.
A keen interest in American sports. (NFL, NBA, MLB, NHL, NCAAB, NCAAF, Tennis or Soccer).
Experience working with AWS S3, Athena, ECS, Cloud Formation, Lambdas & Cloudwatch.
Qualifications:
A degree (PhD, MSc, BSc) in a STEM subject or similar provable numerate and quantitative skills.
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