Soccer Data Scientist

Swish Analytics

$130K *
Business Services
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Masters degree in Data Analytics, Data Science, Computer Science or related field
  • Over 2 years of experience developing production-scale models in Soccer or sports betting
  • Proficient in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, and Markov Chain Monte Carlo methods
  • 5+ years of experience creating and delivering machine learning or statistical models for sports or betting
  • Skilled in SQL and Python
  • Familiar with GitHub and CI/CD processes
  • Experience in AWS environments
  • Strong leadership capabilities and problem-solving skills
  • Exceptional communication skills for diverse audiences

Responsibilities

  • Ideate and improve machine learning and statistical models for sports betting products
  • Develop targeted feature sets using sports-specific knowledge
  • Contribute across all model development stages including proof-of-concept and deployment
  • Enhance model performance through in-depth experiments
  • Analyze outputs to evaluate and refine model performance
  • Follow software engineering best practices and use shared code repositories
  • Document modeling work and effectively communicate results to stakeholders

Benefits

  • Remote work opportunity from anywhere in the USA
  • Ownership and impact on core data product development
  • Collaboration with cross-functional teams
  • Opportunity for professional growth in a fast-paced environment
Full Job Description
In order to be considered for this role, after clicking "Apply Now" above and being redirected, you must fully complete the application process on the follow-up screen.

Job Description

Swish Analytics is looking for a Soccer Data Scientists to join our ever-growing team! Data Science is at the core of our business, so this team has true ownership and impact over developing core components of Swish's data products. This position is remote from the USA.

Duties:
  • 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 sports specific domain knowledge.
  • 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:
  • 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 for 2+ years
  • Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods
  • 5+ 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

Base Salary: Starting at $130,000

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