Full-Time

Rust Engineer

Updated on 11/15/2024

Swish Analytics

Swish Analytics

51-200 employees

Sports analytics and optimization tools provider

Fintech
AI & Machine Learning

Compensation Overview

$100k - $175kAnnually

Junior, Mid

Remote in USA

Category
Backend Engineering
Software Engineering
Required Skills
Rust
Python
SQL
Data Analysis
Requirements
  • Bachelor's Degree in Computer Science, Data Science or similar major
  • Minimum of 1 year of software engineering experience with Rust; 3 years preferred
  • Minimum of 3 years of experience developing high-performance, scalable, and reliable production systems
  • Data Extraction, Wrangling and Analysis in Python
  • Strong SQL querying skills
  • Ability to work independently and take initiative
Responsibilities
  • Develop high-performance and low-latency products to verify results and provide reliability for in-game play
  • Write Rust code, that's sophisticated, fast, and readable for complex, data science infrastructure
  • Design core, backend software components, and code primarily using Rust
  • Building internal and external tools to support Swish’s live trading platform
  • 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
  • Proactively improve our Rust and Python codebase
  • Production model feature deep dives to explain project market lines

Swish Analytics specializes in sports analytics and optimization tools specifically for daily fantasy sports and sports betting in the U.S. market, focusing on major leagues like the NFL, MLB, NBA, and NHL. The company uses an advanced machine learning system to analyze large datasets, providing users with accurate sports predictions and optimized lineups. This helps individual sports bettors, daily fantasy players, and professional betting operators make informed decisions about their bets and fantasy picks. Swish Analytics differentiates itself by being an Authorized MLB Data Distributor, establishing trust and credibility in the industry. The company operates on a subscription-based model, offering a free trial and various plans that cater to different user needs. The goal of Swish Analytics is to maximize return on investment for its clients by identifying not only winning bets but also the most strategic bets, balancing risk and reward for long-term success.

Company Stage

Series B

Total Funding

$6.5M

Headquarters

San Francisco, California

Founded

2014

Growth & Insights
Headcount

6 month growth

16%

1 year growth

28%

2 year growth

70%
Simplify Jobs

Simplify's Take

What believers are saying

  • Swish Analytics' machine learning system can significantly improve users' ROI by identifying the smartest bets, making it highly attractive for serious sports bettors.
  • Partnerships with major leagues and sportsbook platforms can lead to increased credibility and market reach.
  • The company's focus on major U.S. sports leagues ensures a large and engaged user base, providing ample growth opportunities.

What critics are saying

  • The highly competitive nature of the sports analytics market means Swish Analytics must continuously innovate to stay ahead.
  • Reliance on partnerships with major leagues and platforms could pose risks if these relationships are disrupted.

What makes Swish Analytics unique

  • Swish Analytics leverages advanced machine learning to provide highly accurate sports predictions, setting it apart from competitors who rely on traditional statistical methods.
  • Their partnership with Major League Baseball as an Authorized MLB Data Distributor gives them exclusive access to high-quality data, enhancing the accuracy of their analytics.
  • The subscription-based model with a free trial option makes their advanced tools accessible to a wide range of users, from casual bettors to professional operators.

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