Tennis Data Scientist

San Francisco, California, United States

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Sports Analytics, Betting, Fantasy SportsIndustries

Requirements

Candidates must possess a Bachelor's degree in Data Analytics, Data Science, Computer Science, or a related technical field, with a Master's degree being highly preferred. Demonstrated experience in developing production-scale models for tennis or sports betting is required, along with expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, and Markov Chain Monte Carlo methods. A minimum of 4+ years of experience developing and delivering effective machine learning and/or statistical models for sports or sports betting business needs is necessary. Proficiency in relational SQL and Python, experience with source control tools like GitHub and CI/CD processes, and familiarity with AWS environments are essential. Strong leadership skills and excellent communication abilities for both technical and non-technical audiences are also required.

Responsibilities

The Tennis Data Scientist will ideate, develop, and improve machine learning and statistical models for Swish's core sports betting product algorithms. Responsibilities include developing contextualized feature sets using sports domain knowledge, contributing to all stages of model development from proof-of-concept to deployment, and continuously enhancing model performance through experimentation. The role involves analyzing results to assess model performance and identify weaknesses, adhering to software engineering best practices, contributing to shared code repositories, and documenting modeling work for presentations to stakeholders.

Skills

Machine Learning

Statistical Modeling

Feature Engineering

Data Analysis

Sports Analytics

Python

SQL

Software Engineering

Experimentation

Data Visualization

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.

San Francisco, CaliforniaHeadquarters

2014Year Founded

$6.5MTotal Funding

EARLY_VCCompany Stage

Fintech, AI & Machine Learning, Financial ServicesIndustries

51-200Employees

Benefits

Remote Work Options

Risks

Increased competition from AI-driven startups could erode Swish Analytics' market share.

Consumer privacy concerns may impact Swish Analytics' data collection practices.

Potential regulation of sports betting advertising could affect Swish Analytics' revenue streams.

Differentiation

Swish Analytics uses proprietary algorithms for accurate sports predictions and optimized lineups.

The company is an Authorized MLB Data Distributor, enhancing its credibility in sports betting.

Swish Analytics offers a subscription model with free trials, attracting diverse user segments.

Upsides

Increased legalization of sports betting in the U.S. expands Swish Analytics' market opportunities.

The rise of AI-driven personalized betting experiences aligns with Swish Analytics' machine learning expertise.

Growing interest in micro-betting offers Swish Analytics a chance to expand its offerings.

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