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NFL Data Scientist

San Francisco, CA - Remote

Company Description 

Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and consumer/enterprise clients.  

Job Description

Swish Analytics is looking for an NFL Data Scientist 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.  

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 football or sports betting
  • Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods
  • 4+ years of demonstrated experience developing and delivering effective machine learning and/or statistical models to serve business needs
  • 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: $107,000-175,000

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Job Profile

Regions

North America

Countries

United States

Benefits/Perks

Equal opportunity employer

Tasks
  • Adhere to software engineering best practices
  • Analyze model performance
  • Contribute to shared code repositories
  • Develop machine learning models
  • Document modeling work
  • Improve statistical models
  • Present to stakeholders
Skills

AWS Bayesian Statistics CI/CD Computer Science Data & Analytics Data engineering Data Science GitHub Inferential Statistics Machine Learning Markov chain monte carlo Mathematics Probability Theory Python Software Engineering Sports betting SQL Statistical Statistical models

Experience

4 years

Education

Computer Science Data Analytics Data Science Master's Statistics

Timezones

America/Anchorage America/Chicago America/Denver America/Los_Angeles America/New_York Pacific/Honolulu UTC-10 UTC-5 UTC-6 UTC-7 UTC-8 UTC-9