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.

• Serve as the global owner for the commercial customer data pillar, with a core focus on accounts and contacts across commercial platforms and systems. • Design, manage, and maintain core customer data views that support business needs across multiple commercial systems. • Lead the structure and ongoing maintenance of the Account and Contact 360 views in partnership with business unit stakeholders and cross functional partners. • Own and maintain the Commercial MDM data structure globally, ensuring account, contact, and related sales data are represented in a streamlined, meaningful, and scalable way. • Drive simplification across Orthopedics commercial data while preserving the functionality required by business users and commercial teams. • Partner with business and technical stakeholders to ensure customer data is visualized and reported with quality, accuracy, and clarity. • Reduce ambiguity and confusion in customer data by establishing clear ownership, definitions, governance, and reporting standards. • Support product governance activities and maintain partnership with the Data Strategies team to ensure alignment across related data and platform initiatives.

• Coach and Develop the Team • Own the Roadmap • Build Cross-Functional Relationships • Drive Marketplace Forecasting • Own Production ML Systems • Establish Best Practices

• Lead, coach, and develop the Salesforce Performance Analytics team • Drive the strategy and evolution of analytics, forecasting, insights, and AI-enabled capabilities • Shape a product and outcome-oriented roadmap aligned to business and Field priorities • Bring an enterprise perspective to analytics decisions while staying closely connected to Field needs • Translate business needs into scalable analytics solutions that improve decision-making and performance • Set team priorities across support, enhancements, and strategic capability-building work • Oversee service tickets, configuration changes, and core data load activities • Drive continuous improvement in platform usability, operational consistency, and team effectiveness • Partner cross-functionally to support platform changes, integration readiness, and adoption • Maintain accountability for platform stability, operational health, and administrator-owned processes