Swish Analytics

• Support production systems and help triage issues during live sporting events • Architect low-latency, real-time analytics systems including raw data collection, feature development and endpoint production • Build new sports betting data products and predictions offerings • Integrate large and complex real-time datasets into new consumer and enterprise products • Develop production-level predictive analytics into enterprise-grade APIs • Contribute to the design and implementation of new, fully-automated sports data delivery frameworks

Role Description We're looking for a senior software engineer to build and own the production systems and shared frameworks behind our modeling platform. You'll work primarily in Python and Rust to keep our real-time products fast, reliable, and scalable. This is a remote position. This is a software engineering role, not a data science role — you'll partner closely with data scientists and own the systems their models run on. We're looking for engineering depth, not modeling. Duties - Build, test, debug, and deploy production-grade components and services powering our real-time sports betting and analytics products. - Own the deployment and operation of your own services on Kubernetes within a larger platform — this is service ownership within a shared ecosystem, not cluster administration or a DevOps function. - Proactively improve and extend our Rust codebase. - Trace and resolve the root causes of data inaccuracies across pipeline dependencies and our Python codebase. - Set up and maintain alerting, monitoring, and observability for the services you own. - Build and maintain the shared frameworks and services that let our models scale in production, and accelerate their adoption across teams. - Apply large-scale data processing techniques to build scalable, innovative sports betting products. - Examine and improve the integration and scaling of our real-time operations, simulations, and experiments. - Develop solutions for open-ended problems where information is incomplete and no precedent exists. Qualifications - Bachelor's degree in Computer Science or a related technical field. - 5–7 years building and shipping production software, with a strong backend / distributed systems focus. - Advanced Python experience (Rust experience strongly preferred). - Comfortable owning your own services in a Kubernetes environment. - Experience setting up alerting and monitoring systems. - Experience with Kafka (or a comparable streaming / event platform). - Proficiency with SQL. - Experience with source control (GitHub) and related CI/CD processes. - Experience working in AWS environments. - Track record of technical leadership and partnering across teams on complex, ambiguous problems. - Strong communication skills with both technical and non-technical audiences. Requirements - Base salary: Starting at $170,000 - DOE. Company Description 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 consumer/enterprise clients.

Role Description The Swish Analytics team is seeking Data Engineers to have a direct impact on the infrastructure and delivery of our core consumer and enterprise data offerings as well as helping support our coverage of non-US sports. We’re a team passionate about accurate predictions and real-time data, and hope you find satisfaction in building new products with the latest and greatest technologies. This is a remote position. - Support production systems and help triage issues during live sporting events - Architect low-latency, real-time analytics systems including raw data collection, feature development and endpoint production - Build new sports betting data products and predictions offerings - Integrate large and complex real-time datasets into new consumer and enterprise products - Develop production-level predictive analytics into enterprise-grade APIs - Contribute to the design and implementation of new, fully-automated sports data delivery frameworks Qualifications - BS/BA degree in Mathematics, Computer Science, or related STEM field - Minimum of 2+ years of demonstrated experience writing production level code (Python) - Proficiency in Python and SQL (preferably MySQL) - Demonstrated experience with Airflow - Demonstrated experience with Kubernetes - Experience building end-to-end ETL pipelines - Experience utilizing REST APIs - Experience with version control (git), continuous integration and deployment, shell scripting, and cloud-computing infrastructures (AWS) - Experience with web scraping and cleaning unstructured data - Knowledge of data science and machine learning concepts - A strong interest in sports and sports betting, with an emphasis on Tennis - An understanding of US-based sports including the NFL, NBA, MLB, NHL, College Football, College Basketball, and the ability to use your knowledge of the sport to inform your work with complex datasets Company Description 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 consumer/enterprise clients.

• Support production systems and help triage issues during live sporting events • Architect low-latency, real-time analytics systems including raw data collection, feature development and endpoint production • Build new sports betting data products and predictions offerings • Integrate large and complex real-time datasets into new consumer and enterprise products • Develop production-level predictive analytics into enterprise-grade APIs • Contribute to the design and implementation of new, fully-automated sports data delivery frameworks

• Build, test, debug, and deploy production-grade components and services powering our real-time sports betting and analytics products • Own the deployment and operation of your own services on Kubernetes within a larger platform — this is service ownership within a shared ecosystem, not cluster administration or a DevOps function • Proactively improve and extend our Rust codebase • Trace and resolve the root causes of data inaccuracies across pipeline dependencies and our Python codebase • Set up and maintain alerting, monitoring, and observability for the services you own • Build and maintain the shared frameworks and services that let our models scale in production, and accelerate their adoption across teams • Apply large-scale data processing techniques to build scalable, innovative sports betting products • Examine and improve the integration and scaling of our real-time operations, simulations, and experiments • Develop solutions for open-ended problems where information is incomplete and no precedent exists

• Ideate, develop and improve machine learning and statistical models that drive Swish’s core algorithms for producing state-of-the-art sports betting products. • Develop contextualized feature sets using specific domain knowledge in soccer. • Contribute to all stages of model development, from creating proof-of-concepts and beta testing, to partnering with data engineering and product teams to deploy new models. • Strive to constantly improve model performance using insights from rigorous offline and online experimentation. • Analyze results and outputs to assess model performance and identify model weaknesses for directing development efforts. • Adhere to software engineering best practices and contribute to shared code repositories. • Document modeling work and present to stakeholders and other technical and non-technical partners.

Role Description Swish Analytics is looking for a Soccer Data Scientist to join our ever-growing team! Data Science is at the core of our business, so this team has true ownership and impact over developing core components of Swish's data products. This position is remote from the USA. - Ideate, develop and improve machine learning and statistical models that drive Swish’s core algorithms for producing state-of-the-art sports betting products. - Develop contextualized feature sets using sports specific domain knowledge. - Contribute to all stages of model development, from creating proof-of-concepts and beta testing, to partnering with data engineering and product teams to deploy new models. - Strive to constantly improve model performance using insights from rigorous offline and online experimentation. - Analyze results and outputs to assess model performance and identify model weaknesses for directing development efforts. - Adhere to software engineering best practices and contribute to shared code repositories. - Document modeling work and present to stakeholders and other technical and non-technical partners. Qualifications - Masters degree in Data Analytics, Data Science, Computer Science or related technical subject area. - Demonstrated experience developing models at production scale for Soccer, or sports betting for 2+ years. - Expertise 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 and/or statistical models to serve business needs in sports or sports betting. - Experience with relational SQL & Python. - Experience with source control tools such as GitHub and related CI/CD processes. - Experience working in AWS environments. - Proven track record of strong leadership skills. Has shown ability to partner with teams in solving complex problems by taking a broad perspective to identify innovative solutions. - Excellent communication skills to both technical and non-technical audiences. Requirements - Base Salary: Starting at $130,000. Company Description 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 consumer/enterprise clients.

Title: Trading Analyst Location: London, Europe - Remote, United Kingdom Job Description: In order to be considered for this role, after clicking "Apply Now" above and being redirected, you must fully complete the application process on the follow-up screen. Company OverviewSwish 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 consumer/enterprise clients. Job Description - This position is 100% Remote Duties: - Manage client risk, ensuring the highest margins on Swish products through +EV decisions - Manage and oversee depth chart accuracy, making time-sensitive adjustments in both prematch & in-play settings - Strategically research & track verified news sources, being the first to uncover important news and understand the overall impact on betting markets - Independently analyze betting trends in a scientific process, turning data into quantifiable trading actions Requirements: - Minimum of 3 years of in-game play experience at an online sportsbook - Deep understanding of sports betting and odds origination - Passion and intimate knowledge of the NBA, NFL, MLB, NHL, and NCAA Basketball + Football - Strong mathematical, statistical, and/or analytical skills – ability to understand and calculate + convert odds on the fly - Results driven work ethic – focused on improving process, results and profitability - Availability to work flexible schedules, including nights, weekends and/or holidays Preferred: - Bachelor’s Degree in a STEM discipline  - An understanding of relational database systems (MySQL) - Experience working with cross functional teams (Data Science teams a plus) 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.

• Cross-functional program leadership • The operating system for delivery • Delivery coordination and predictability • Delivery maturity across the org • Team leadership

• Lead the onboarding and offboarding processes, ensuring a seamless and positive experience for all employees. • Partner with the Talent Acquisition team to support the hiring process. • Analyze HR metrics and prepare reports to support management decision-making regarding staffing, turnover, and cost analysis. • Awareness and support mediating and resolving disputes, disagreements, and conflicts between employees, or between employees and management. • Support fair, consistent, and legally compliant application of the company's disciplinary procedures, up to and including termination. • Manage and execute the end-to-end payroll process for all US and international employees (including contractors) using our current payroll systems. • Ensure accurate and timely processing of salaries, deductions, taxes, and statutory contributions, adhering to local, state, federal, and international regulations. • Maintain meticulous employee records, ensuring data integrity and compliance across all HR systems. • Serve as the primary internal resource for HR compliance, staying current on all relevant US labor laws (federal and state) and international employment legislation.