- Turning modeling ideas into production software
- Improve the reliability and performance of production modeling code
- Adhere to software engineering best practices
- Bachelor degree in computer science, mathematics or statistics
- Minimum of 4 years of relevant experience
- Extensive knowledge of MLB, NBA, and NFL rules and game play is a must
- Experience with code control tools, such as git, in a unix environment
- Demonstrated experience of data structures and algorithms
- Demonstrated experience of probability, statistics, and machine learning
- Demonstrated scientific or data oriented experience in Python
- Demonstrable experience in C/C++/Rust (at least one)
- Strong technical communication skills
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Model Based System Engineer
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Sports Modeling Engineer - San Francisco, United States - teamworkonline
Description
Company Overview
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 looking to hire a Sports Modeling Engineer to join our ever-growing team This engineer will work closely with data scientists to build reliable, high-performance software at the core of Swish's product offering. Ideal candidates will have a solid understanding of popular US sports (football, basketball, baseball) and experience writing performance critical code.
Responsibilities:
Requirements:
$133,000 - $175,000