Soccer Data Scientist

Swish Analytics

Soccer Data Scientist developing predictive models for sports betting products at Swish Analytics. Contributing to all stages of model development with a focus on soccer data.

Posted 7/14/2026full-timeRemote • 🇬🇧 United KingdomMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and improving machine learning and statistical models specifically for sports betting, with a strong foundation in Probability Theory and Inferential Statistics. Proven ability to collaborate with cross-functional teams and communicate complex concepts effectively to diverse audiences.

Highest-signal resume keywords

Machine Learning Model DevelopmentStatistical ModelingPython ProgrammingAWS Environment ExperienceLeadership Skills

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Probability TheoryInferential StatisticsBayesian StatisticsMarkov Chain Monte Carlo MethodsSQL

Soft Skills

Excellent Communication SkillsProblem-Solving

Tools & Technologies

GitHubCI/CD Processes

Certifications & Qualifications

Masters Degree in Data AnalyticsMasters Degree in Data ScienceMasters Degree in Computer Science

Industry Keywords

Sports BettingSoccerModel Performance Analysis

Tech Stack

Tools & technologies

AWSPythonSQL

About the role

Key responsibilities & impact

Ideate, develop and improve machine learning and statistical models that drive Swish’s core algorithms for producing state-of-the-art sports betting products.
Develop contextualized feature sets using specific domain knowledge in soccer.
Contribute to all stages of model development, from creating proof-of-concepts and beta testing, to partnering with data engineering and product teams to deploy new models.
Strive to constantly improve model performance using insights from rigorous offline and online experimentation.
Analyze results and outputs to assess model performance and identify model weaknesses for directing development efforts.
Adhere to software engineering best practices and contribute to shared code repositories.
Document modeling work and present to stakeholders and other technical and non-technical partners.

Requirements

What you’ll need

Masters degree in Data Analytics, Data Science, Computer Science or related technical subject area
Demonstrated experience developing models at production scale for soccer or sports betting
Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods
Minimum of 3+ years of demonstrated experience developing and delivering effective machine learning and/or statistical models to serve business needs in sports or sports betting
Experience with relational SQL & Python
Experience with source control tools such as GitHub and related CI/CD processes
Experience working in AWS environments etc
Proven track record of strong leadership skills.
Has shown ability to partner with teams in solving complex problems by taking a broad perspective to identify innovative solutions
Excellent communication skills to both technical and non-technical audiences.

Benefits

Comp & perks

Remote work options