Full-Time

Product Engineer

Confirmed live in the last 24 hours

Swish Analytics

Swish Analytics

51-200 employees

Sports analytics and optimization tools provider

Fintech
AI & Machine Learning
Financial Services

Compensation Overview

$133k - $180kAnnually

Senior, Expert

Remote in USA

Category
Backend Engineering
Software QA & Testing
Software Engineering
Required Skills
Rust
Python
Data Science
Git
SQL
Machine Learning
AWS
Risk Management
Data Analysis

You match the following Swish Analytics's candidate preferences

Employers are more likely to interview you if you match these preferences:

Degree
Experience
Requirements
  • Bachelor degree in Computer Science, Applied Math, Data Analytics, Data Science or related technical subject area; Master degree highly preferred
  • 5+ years of demonstrated experience developing and delivering effective machine learning and/or statistical products to serve business needs
  • Knowledge in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods
  • Advanced Python & SQL
  • Experience with source control tools such as GitHub and related CI/CD processes
  • Experience working in AWS environments
  • 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
Responsibilities
  • Expand utilization and adoption of existing models and accelerate adoption of commonly used proprietary frameworks.
  • Establish and refine KPI's and OKR's for scaling and accelerating the product offerings.
  • Experience applying large scale data processing techniques to develop scalable and innovative sports betting products.
  • Proactively improve our Rust codebase
  • Source origins of data inaccuracies through data pipeline dependencies and Python code base
  • Use extensive experience to build, test, debug, and deploy production-grade components
  • Keep up to date with new approaches to inferential statistics, sampling, and experimental design.
  • Examine the integration and scaling of our real world operations, simulations, experiments, and demonstrations.
  • Expert Python developer using many different machine learning and data science frameworks.
  • Provide risk management guidance on methods for assessing and mitigating risk.
  • Skill in developing or recommending analytic approaches or solutions to problems and situations for which information is incomplete or for which no precedent exists.
  • Adhere to software engineering best practices and contribute to shared code repositories.

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. Their goal is to maximize return on investment for clients by identifying the best bets while balancing risk and reward. Users can access their services through a subscription model, starting with a free trial and offering various plans for different levels of access.

Company Stage

Seed

Total Funding

$6.5M

Headquarters

San Francisco, California

Founded

2014

Growth & Insights
Headcount

6 month growth

-2%

1 year growth

-7%

2 year growth

-7%
Simplify Jobs

Simplify's Take

What believers are saying

  • 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.

What critics are saying

  • 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.

What makes Swish Analytics unique

  • 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.

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Benefits

Remote Work Options