Data Scientist
Sardine150,000 - 170,000 USD/year
- Full Time
- Senior (5 to 8 years)
$120,000 – $175,000Compensation
Junior (1 to 2 years)Experience Level
Full TimeJob Type
UnknownVisa
Sports Analytics, Data Science, Betting & Fantasy SportsIndustries
Requirements
Candidates are required to possess a Master's degree in Data Analytics, Data Science, Computer Science, or a related technical subject area, with a PhD being highly preferred. They must have demonstrated experience developing models at production scale for baseball or sports betting, along with expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, and Markov Chain Monte Carlo methods. A minimum of four years of experience developing and delivering effective machine learning and/or statistical models to meet business needs in sports or sports betting is also required, alongside proficiency in relational SQL and Python, experience with source control tools like GitHub, and familiarity with AWS environments.
Responsibilities
The Basketball Data Scientist will ideate, develop, and improve machine learning and statistical models to 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 proof-of-concepts to deployment, analyze results and outputs to assess model performance and identify weaknesses, adhere to software engineering best practices and contribute to shared code repositories, and document modeling work and present findings to stakeholders and other partners.
Skills
Machine Learning
Statistical Modeling
Data Analysis
Feature Engineering
Model Deployment
Software Engineering Best Practices
Data Visualization
Programming (likely Python/R/SQL)
Swish Analytics
Sports analytics and optimization tools provider
About Swish Analytics
Swish Analytics specializes in sports analytics and optimization tools for daily fantasy sports and sports betting, focusing on major U.S. leagues like the NFL, MLB, NBA, and NHL. The company uses an advanced machine learning system to analyze large datasets, providing accurate sports predictions and optimized lineups. This helps users, including individual bettors and professional operators, make informed decisions about their bets and fantasy picks. Swish Analytics differentiates itself by being an Authorized MLB Data Distributor, establishing trust in the sports betting community. Operating on a subscription-based model, users can access various levels of tools and analytics, starting with a free trial. The goal of Swish Analytics is to maximize return on investment for clients by identifying the best bets and balancing risk and reward for long-term success.
Key Metrics
San Francisco, CaliforniaHeadquarters
2014Year Founded
$6.5MTotal Funding
EARLY_VCCompany Stage
Fintech, AI & Machine Learning, Financial ServicesIndustries
51-200Employees