Swish Analytics

Basketball Data Scientist

San Francisco, California, United States

$120,000 – $175,000Compensation
Junior (1 to 2 years)Experience Level
Full TimeJob Type
UnknownVisa
Sports Analytics, Data Science, Betting & Fantasy SportsIndustries

Position Overview

  • Location Type: Remote
  • Employment Type: Full-time
  • Salary: $120,000 - $175,000 (encompasses multiple levels and depends on experience)

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 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.

Responsibilities

  • 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; PhD highly preferred.
  • Demonstrated experience developing models at production scale for baseball 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.

Company Information

Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products.

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.

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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