Job Title: Data Scientist
Location: Bath, UK
StatsBomb Services was founded in January 2017 offering Analytics and Consultancy primarily to football clubs. We work with clubs from all over the world, our direct contacts range from field level analysts and coaches to directors of football, CEOs, and owners. StatsBomb also has a history of producing new research, visualisations, and insights into the game of football.
The Data Scientist Role
StatsBomb is looking for a highly-skilled data scientist to join our growing company. The ideal candidate will have an interest in football/soccer data, and have demonstrated portfolios of past work. The position is full time and requires being in our Bath office 3 days a week on average, but the other two days you are free to work wherever you like. This level of freedom requires you to be a self-starter, to problem solve with only moderate oversight, and to continuously produce new material, data, and analysis in a clean and accessible way.
A large part of your job will be furthering the work of StatsBomb. This includes practical areas like player and team evaluation, and less immediately applicable things like analysis to understand data sets and how they vary across data providers. You should also expect to inherit and improve existing models like xG, passing ability, finishing ability, etc. If your comfort level working with GLMs, random forests, and general Bayesian approaches is low, this might not be the job for you.
- BSc in a quantitative subject or equivalent proof of experience.
- Comfortable with a range of classical statistical models (eg. linear, GLM, random forests, clustering techniques)
- Advanced computer programming and software development. (Python skills strongly preferred, or experience with R and AT LEAST one other language.)
- Good SQL skills
- Excellent communication skills, both written and verbal
- Basic visualisation skills in Tableau/d3js/ggplot/SVG
- Basic understanding of football
- Self-starter, self-motivated, hard-working
- MSc/PhD in a quantitative subject
- Comfortable with R's data analysis stack (tidyverse)
- Data analysis packages in Python (scipy, pandas, scikit-learn)
- Source control and collaboration with Git
- Unix command line skills
- Experience with developing for production
- Experience with Bayesian analysis, ideally using Stan
- Deep learning experience
Based on experience and will include a competitive stock option package
Please send an email to email@example.com with the subject “Data Scientist Position” and include a cover letter (email body), resume/CV including any links to GitHub or other publicly available projects, and answers to the following questions:
- When will you be available to start?
- Assume you have the best event data in the world available to you, but no tracking data. What question do you want to answer first and how would you go about doing so? Why is your methodology a better approach than other ones? (Don’t write a book. Being able to answer questions concisely is an important part of the job.)
- What are your hobbies? Are you any good at them? How do you know?