Develop and improve machine learning and statistical models to drive core algorithms for sports betting products. Collaborate with data engineering and product teams to deploy models and optimize performance through rigorous experimentation.
Swish Analytics
13 Remote Job Openings at Swish Analytics
Develop and improve machine learning and statistical models to drive core algorithms for sports betting products. Create contextualized soccer feature sets and collaborate with engineering teams to deploy models into production.
Manage client risk and ensure high margins through positive expected value decisions and depth chart accuracy. Research news sources and analyze betting trends to execute quantifiable trading actions.
The Director of Project Management will build and lead the PMO to establish the operational backbone for coordinated delivery across the company. This includes owning cross-functional programs across Trading, Engineering, and Data Science while evolving the frameworks for planning, prioritization, and release cadence.
Lead global people operations including end-to-end payroll, benefits administration, and HR compliance across multiple US states and international jurisdictions. Serve as the primary resource for employee relations, policy management, and the onboarding/offboarding process.
Establish and lead the company's PMO to build an operational backbone for coordinated delivery across technical departments. Own the frameworks for planning, prioritization, and tracking to ensure predictable execution of cross-functional programs.
Manage client risk and ensure high margins through positive expected value decisions. Oversee depth chart accuracy and analyze betting trends to execute quantifiable trading actions.
The analyst will work with data scientists and engineers to diagnose data pipeline integrity issues and detect inaccuracies in on-field data. They will also define validation tests, research roster statuses, and support feature development for predictive models.
Monitor live sports markets and refine pricing models using statistical analysis and market signals. Manage real-time trading risk and collaborate with engineering teams to improve pricing infrastructure and execution tools.
This is an open application inviting talented individuals passionate about sports, data, and building great products to connect with the growing company. The team will keep submitted information on file for future opportunities as they arise across various functions.
The Senior Quantitative Researcher will own end-to-end research and production pipelines for trading strategies, leading alpha research initiatives using advanced statistical and machine learning techniques. Responsibilities also include building risk monitoring systems, developing models for position sizing and portfolio optimization, and guiding junior researchers.
The engineer will design, prototype, implement, evaluate, and optimize systems to generate highly accurate, low-latency sports datasets and predictions. They will also build, test, deploy, and maintain production systems while optimizing the data scientist's modeling workflow.
The role involves ideating, developing, and improving machine learning and statistical models that drive core algorithms for state-of-the-art sports betting products. Responsibilities also include contributing to all stages of model development, from proof-of-concepts to deployment, and constantly improving performance through rigorous experimentation.
