Tennis Data Scientist

Swish Analytics

$135K — $190K *
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 in model development for Tennis or sports betting
  • Strong expertise in Probability Theory, Machine Learning, and Inferential Statistics
  • 5+ years delivering machine learning/statistical models for business needs in sports
  • Proficient in SQL & Python programming languages
  • Familiarity with GitHub and CI/CD processes
  • Experience in AWS environments
  • Demonstrated leadership capabilities in cross-functional team collaborations
  • Effective communication skills for technical and non-technical audiences

Responsibilities

  • Ideate, develop, and enhance machine learning and statistical models for sports betting
  • Create customized feature sets utilizing domain knowledge in Tennis
  • Contribute throughout model development stages from concept to deployment
  • Continuously improve model performance through detailed experimentation
  • Analyze model outcomes to identify weaknesses and areas for enhancement
  • Follow software engineering best practices in code contributions
  • Document processes and present findings to various stakeholders

Benefits

  • Fully remote work environment
  • Ownership and impact in developing core data products
  • Collaborative culture within a sports analytics-focused team
  • Opportunities for innovation in sports betting algorithms
  • Access to cutting-edge machine learning and statistical development techniques
Full Job Description
Job Description

Swish Analytics is looking for a Tennis 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 Tennis 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: $135,000 - $190,000

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

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