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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.
As a Customer Success Associate at Swish Analytics, you will manage client inquiries, identify customer issues, and communicate with various teams to provide solutions. You will leverage your understanding of sports betting and analytics to enhance the customer experience while delivering results-driven support.
As a Customer Success Associate, you will communicate Swish's products and manage client inquiries through various channels. You will identify customer challenges and collaborate with internal teams to offer solutions, contributing to client satisfaction and process improvement.
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.
Develop high-performance, low-latency products in Rust, design backend software components, debug production-grade systems, and improve existing codebases while analyzing data accuracy and supporting trading platforms.
As an NFL Data Scientist, you will develop and improve machine learning and statistical models for sports betting products. Responsibilities include model development, feature set creation, performance analysis, documentation, and collaboration with data engineering and product teams.
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.
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