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Below covers everything you need to know about what this opportunity entails, as well as what is expected from applicants. Get AI-powered advice on this job and more exclusive features. Swish Analytics is looking for a Product Engineer, to join our ever-growing team! Science is at the core of our business, and our Research & Experimentation branch works to create enhancements for future generation products, scale internal tools as our team and customers continue to grow, and set the stage for making big bets on new products and features. This is a great opportunity to work with thought leaders in the Sports Data space to create new and transformative products. Duties include expanding utilization and adoption of existing models and accelerating adoption of commonly used proprietary frameworks; establishing and refining KPIs and OKRs for scaling and accelerating the product offerings; applying large scale data processing techniques to develop scalable and innovative sports betting products; proactively improving the Rust codebase; sourcing origins of data inaccuracies through data pipeline dependencies and Python code base; building, testing, debugging, and deploying production-grade components; keeping up to date with new approaches to inferential statistics, sampling, and experimental design; examining the integration and scaling of real world operations, simulations, experiments, and demonstrations; expert Python development using many different machine learning and data science frameworks; providing risk management guidance on methods for assessing and mitigating risk; developing or recommending analytic approaches or solutions to problems and situations for which information is incomplete or for which no precedent exists; adhering to software engineering best practices and contributing to shared code repositories. Requirements include a 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 skills; 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; excellent communication skills to both technical and non-technical audiences. Seniority level Seniority levelMid-Senior level Employment type Employment typeFull-time Job function Job functionEngineering and Information Technology Referrals increase your chances of interviewing at Swish Analytics by 2x Sign in to set job alerts for “Product Engineer” roles. South San Francisco, CA $95,000.00-$115,000.00 3 months ago San Mateo, CA $95,000.00-$280,000.00 2 weeks ago Alameda, CA $95,000.00-$134,000.00 2 days ago San Francisco, CA $140,000.00-$200,000.00 9 months ago Entry Level Mechanical Engineer, application via RippleMatch San Francisco, CA $140,000.00-$200,000.00 1 month ago South San Francisco, CA $120,000.00-$145,000.00 3 months ago San Francisco, CA $150,000.00-$200,000.00 11 months ago San Francisco, CA $175,000.00-$280,000.00 2 weeks ago San Mateo, CA $195,000.00-$255,000.00 7 months ago San Francisco, CA $80,000.00-$160,000.00 3 weeks ago Entry Level Industrial Engineer, application via RippleMatch San Francisco, CA $180,000.00-$215,000.00 2 weeks ago San Leandro, CA $140,000.00-$190,000.00 7 months ago San Francisco, CA $147,000.00-$242,000.00 1 month ago San Francisco, CA $120,000.00-$240,000.00 7 months ago San Francisco, CA $60,000.00-$120,000.00 1 month ago San Francisco, CA $140,000.00-$220,000.00 2 months ago Manufacturing Engineer, application via RippleMatch San Francisco, CA $130,000.00-$200,000.00 1 month ago San Francisco, CA $140,000.00-$170,000.00 2 months ago San Francisco, CA $125,000.00-$200,000.00 1 month ago San Francisco, CA $175,000.00-$280,000.00 2 weeks ago We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.

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