Search the 11 jobs at Swish Analytics

As a Data Scientist on the Trading Analytics team, you'll develop and improve machine learning and statistical models for sports betting products. Duties include automating trading suggestions, enhancing model performance, and collaborating with teams to deploy models while adhering to best practices in software engineering.

As a UX Designer at Swish Analytics, you'll collaborate with Product Managers and engineers to create user interfaces for a trading platform. Your role includes developing high-fidelity prototypes, managing design projects, and ensuring consistency and quality across products, all while thriving in a fast-paced environment.

The Frontend Engineer will design and develop a data analytics platform, standardizing processes for development, coordinating with various departments for deployment, and ensuring high-quality software production. They will leverage their experience with JavaScript and RESTful API development, among other technologies, to drive project success.

As a Soccer Data Scientist at Swish Analytics, you will ideate and improve machine learning and statistical models, develop feature sets leveraging soccer domain knowledge, and contribute to model deployment while striving to enhance model performance. You'll analyze results and communicate findings clearly to diverse stakeholders.

As a Tennis Data Scientist, you will develop and enhance machine learning models for sports betting products, analyze and assess model performance using rigorous experimentation, and collaborate with engineering and product teams to deploy new models, all while adhering to software engineering best practices.

As a Staff Software Engineer, you will lead the development of core backend applications, perform code reviews, optimize applications, and design new services. You'll work with distributed data, collaborate on architectural diagrams, and ensure high-performance APIs while adhering to coding standards.

The Product Engineer at Swish Analytics will enhance and scale existing data products, develop effective machine learning and statistical solutions, improve Rust and Python codebases, and establish KPIs for product offerings. They will work closely with teams to address complex challenges and ensure high-quality data processes for predictive sports analytics.

The DevOps Engineer at Swish Analytics will develop and maintain Kubernetes clusters for ML workloads, work with Data Science and Engineering teams to optimize deployments, enforce software management best practices, and monitor system reliability. They will also respond to incidents and provide on-call support as needed.

As a Senior Trading Analyst, you will manage client risk, oversee depth chart accuracy, research news sources for impact on betting markets, and analyze betting trends to convert data into trading actions.

The Basketball Data Scientist will develop and improve machine learning and statistical models for sports betting products at Swish Analytics. Responsibilities include creating features using sports knowledge, testing and deploying models, analyzing performance, adhering to software practices, and documenting work to share with stakeholders.

The NFL Data Scientist will ideate and develop machine learning and statistical models for sports betting products. This role involves creating feature sets, collaborating with teams on model deployment, conducting experiments to improve model performance, analyzing outputs for weaknesses, documenting work, and presenting findings to various stakeholders.