Basketball Data Scientist

Swish Analytics

$130K *
US-AnywhereRemote in San Francisco, CA
Hospitality & Recreation
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Data Analytics, Data Science, Computer Science, or equivalent; Masters preferred
  • 4+ years of experience in developing production-scale models for Basketball or sports betting
  • Proficiency in Probability Theory, Machine Learning, Inferential and Bayesian Statistics, Markov Chain Monte Carlo methods
  • Strong technical skills in SQL and Python
  • Familiarity with version control using GitHub and CI/CD processes
  • Experience in AWS cloud environments
  • Demonstrated leadership ability in cross-functional team settings
  • Excellent communication skills tailored for diverse audiences

Responsibilities

  • Ideate and enhance machine learning and statistical models for sports betting products
  • Develop contextual feature sets using specialized sports knowledge
  • Engage in all phases of model development, including proof-of-concepts and deployment
  • Enhance model performance based on rigorous experimentation
  • Analyze results to improve model performance and identify weaknesses
  • Follow software engineering best practices and contribute to collaborative code repositories
  • Document modeling processes and present findings to various stakeholders

Benefits

  • Fully remote working environment
  • Opportunity for true ownership and impactful work in core data products
  • Collaborative and supportive team culture
  • Exposure to cutting-edge sports data technologies
  • Professional growth and development opportunities
Full Job Description
Job Description

Swish Analytics is hiring Basketball 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. We're hiring a Data Scientist to support our Sports Data Models

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:
  • Bachelor's degree in Data Analytics, Data Science, Computer Science or related technical subject area; Masters highly preferred
  • Demonstrated experience developing models at production scale for Basketball or sports betting
  • Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods
  • Minimum of 4+ 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 NBA Team Locations San Francisco, CA - Remote Remote status Fully Remote

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