Data Scientist II (Soccer)

Teamworks

17d•$83,000 - $145,000

About The Position

We're hiring a Data Scientist II on our Soccer team to develop the statistical and machine learning models our partner clubs use for player recruitment. Our team primarily focuses on building models using both player tracking data and event data to identify undervalued players and characterize the skills that make them effective. The work supports high-stakes recruitment decisions for professional clubs across global football. The team is managing growing demand from partner clubs alongside model maintenance and new development. This hire will take ownership across the model lifecycle, from design and validation through deployment and improvement. That added capacity will help us move important initiatives forward while keeping our existing models accurate and reliable.

Requirements

3+ years of professional or research experience writing code in R or Python for data science, statistics, or machine learning work
Comfort with SQL for building and querying structured data
Strong data science fundamentals: you understand how models work, what they need from the data, and how to set data up to support them
Experience working with sports tracking data, including understanding the kinds of models typically built and the data challenges that come with them
Strong communication skills — you'll be explaining modeling decisions directly to partner clubs, not just internal teammates

Nice To Haves

Direct experience with soccer data or soccer analytics (inside a team, public work, or academically)
A demonstrated track record of tackling hard problems through published research, blog posts, conference talks, or public projects
Experience using a cloud compute provider (e.g. AWS or Google Cloud) to train and deploy models
Comfort using AI coding tools, paired with the judgment to recognize when their output needs to be questioned or corrected

Responsibilities

Develop statistical and machine learning models that help professional soccer clubs identify undervalued players and strong recruitment targets
Use player tracking data to build spatio-temporal models that quantify player impact and skill
Build metrics and analyses that soccer teams rely on to make decisions, and support client-facing work by building tools to support model interpretation and understanding
Validate models and outputs — your own and others’ — with enough rigor that the team can trust what ships
Write clear reports that communicate technical work to clients
Partner with our engineering team to deploy models on cloud infrastructure and turn strong analytical work into reliable production systems
Review code from other data scientists, share constructive feedback, and contribute ideas that advance the team's work