Search the 8 jobs at Swish Analytics

As a Staff Software Engineer at Swish Analytics, you will lead the development of backend applications, conduct code reviews, optimize existing services, and work on architectural designs. You will need to manage high-traffic APIs while collaborating on global data solutions.

The Senior Trading Analyst at Swish Analytics will manage client risk, oversee depth chart accuracy, and conduct strategic research on betting trends. The role requires a strong understanding of sports betting and the ability to turn data into actionable insights while working flexibly to cover various schedules.

The DevOps Engineer will develop and maintain Kubernetes clusters for ML workloads, implement CI/CD pipelines, and collaborate with Data Science and Engineering teams to enhance system reliability and scalability. Responsibilities include monitoring systems, responding to incidents, and enforcing best practices in software deployment.

The NFL Data Scientist will develop and improve machine learning and statistical models for Swish's sports betting products, analyze model performance, and collaborate with data engineering and product teams. Responsibilities include rigorous experimentation and documenting model development.

The Tennis Data Scientist will develop and enhance machine learning and statistical models for predictive sports analytics products. Responsibilities include improving model performance through experimentation, analyzing results to identify weaknesses, and collaborating with other teams for model deployment while documenting work for stakeholders.

As a Frontend Engineer, you will design and develop a next-generation data analytics platform, standardize development processes, collaborate with stakeholders for technical requirements, and ensure smooth project delivery from development through deployment. Producing high-quality software through testing and automation is key to this role.

Swish Analytics is seeking a Research & Experimentation Scientist to accelerate progress on sports betting algorithms and models, apply large scale data processing techniques, stay updated on inferential statistics, and provide risk management guidance. The role requires advanced Python and SQL skills, knowledge in Probability Theory, Machine Learning, and Bayesian Statistics, as well as experience in AWS environments.

Hiring Basketball Data Scientists to develop machine learning and statistical models for sports betting products. Responsibilities include model development, feature set creation, model performance improvement, and collaboration with teams. Requires a Master's degree, expertise in Probability Theory and Machine Learning, and experience in SQL, Python, and AWS.