Soccer Data Scientist

San Francisco, California, United States

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$100,000 – $175,000Compensation

Junior (1 to 2 years)Experience Level

Full TimeJob Type

UnknownVisa

Sports Analytics, Data Science, Betting & Fantasy SportsIndustries

Requirements

Candidates must possess a Master’s degree in Data Analytics, Data Science, Computer Science, or a related technical field, and have at least three years of demonstrated experience developing and delivering effective machine learning and/or statistical models for sports or sports betting, with expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, and Markov Chain Monte Carlo methods. Applicants should also have experience with relational SQL and Python, as well as experience with source control tools like GitHub and CI/CD processes, and familiarity with AWS environments.

Responsibilities

The Soccer Data Scientist will ideate, develop, and improve machine learning and statistical models to drive Swish’s core algorithms for sports betting products, develop contextualized feature sets utilizing specific soccer domain knowledge, contribute to all stages of model development from proof-of-concept creation to deployment, analyze model performance and identify weaknesses, adhere to software engineering best practices, document modeling work, and present findings to stakeholders and partners.

Skills

Machine Learning

Statistical Modeling

Data Analysis

Feature Engineering

Model Deployment

Experimentation

Software Engineering Best Practices

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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