Soccer Data Scientist

Swish Analytics

$130K *
US-AnywhereRemote in San Francisco, CA
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
  • 2+ years of experience developing models in Soccer or sports betting
  • Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, and Markov Chain Monte Carlo methods
  • 5+ years of experience delivering machine learning/statistical models in sports
  • Proficiency in relational SQL & Python
  • Familiarity with source control (GitHub) and CI/CD processes
  • Experience in AWS environments
  • Strong leadership and problem-solving skills
  • Excellent communication skills for diverse audiences

Responsibilities

  • Ideate and improve machine learning/statistical models for sports betting
  • Develop feature sets using domain knowledge in sports
  • Contribute to all stages of model development including proof-of-concepts
  • Enhance model performance through offline and online experimentation
  • Analyze model outputs to identify weaknesses and direct development
  • Adhere to software engineering best practices and share code
  • Document modeling work and present findings to various stakeholders

Benefits

  • Fully remote work opportunity from anywhere in the USA
  • Ownership and impact in developing core data products
  • Collaborative team environment with opportunities for innovation
  • Engagement with cutting-edge technology in data science and sports analytics
  • Flexible work arrangements
Full Job Description
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

Department Data Science Role Soccer Team Locations San Francisco, CA - Remote Remote status Fully Remote

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