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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 enterprise clients.
The Data Science team is hiring an experienced Machine Learning Engineer with a background building machine learning and statistical modeling frameworks from scratch. They can assist with optimizing the different aspects of the modeling process (Data Validation, Data Visualization, Data Stores & Structures, Feature Engineering, Model Training & Evaluation, Deployments) and improving a variety of Swish products. They will know when to “roll your own” and when to outsource a particular step in the modeling process. They will engineer custom solutions to solve complex data-related sports challenges across multiple leagues.
This position is 100% remote
- Design, prototype, implement, evaluate, optimize and monitor machine learning algorithms and related software systems to generate sports datasets and predictions with high accuracy and low latency
- Evaluate internal modeling frameworks and tools to optimize data scientist's modeling workflow
- Build, test, deploy and maintain production systems
- Maintain and promote best practices for software development, including deployment process, documentation, and coding standards
- Contribute to technical and product discussions, and share knowledge and ideas with colleagues across the company
- Masters degree in Computer Science, Applied Mathematics, Data Science, Computational Physics/Chemistry or related technical subject area; PhD degree preferred
- Demonstrated experience developing data science modeling systems and infrastructure that scales
- Proficient in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods
- 5+ years of demonstrated experience developing and delivering effective machine learning models to serve business needs
- Experience with Python and modern machine learning frameworks
- Affinity for teamwork and collaboration with others to solve problems, share knowledge, and provide feedback
- Strong communication skills when discussing technical concepts with technical and non-technical colleagues
Base salary: $133,000-180,000
Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer’s discretion, this position may require successful completion of background and reference checks.