Sports Analytics Data Scientist

Sporting Kansas City; Kansas City (KS); On-site; USD 110,000 - 160,000; Full time

Job summary

Sporting Kansas City is seeking a Data Scientist to design, validate and deploy advanced models that influence decision-making across medical, sports science, scouting and performance analysis. You will translate complex data into actionable insights and help build predictive frameworks with production-ready workflows.

The role requires collaboration with coaches, analysts and engineers, and a proactive approach to leveraging data for squad planning, player availability and load management in a

Qualifications

• Bachelor's degree in computer science, data science or related STEM field.
• Experience in Data Science, ML, Applied Statistics.
• Proven experience designing, validating and monitoring ML models.
• Strong SQL and Python for data analysis.
• Knowledge of statistical modelling and experimental design.
• Excellent communication and collaboration skills.
• Experience in elite soccer or high-performance sports preferred.

Responsibilities

• Lead end-to-end development of advanced modelling projects from problem definition to deployment.
• Develop tools for testing, validation, monitoring, and governance.
• Collaborate with coaches, analysts and engineers to translate insights into decisions.
• Ensure model outputs are understandable and actionable for stakeholders.
• Maintain robust data workflows and production-ready pipelines.
• Stay current with data science best practices and industry trends.

Skills

SQL

Python

Statistical modelling

Communication skills

Problem solving

Education

Bachelor's degree in CS/DS/related STEM

Tools

Tableau

Cloud platforms

Job description

Sporting Kansas City is seeking a Data Scientist to design, validate and deploy advanced models that influence decision-making across medical, sports science, scouting and performance analysis. You will translate complex data into actionable insights and help build predictive frameworks with production-ready workflows.

The role requires collaboration with coaches, analysts and engineers, and a proactive approach to leveraging data for squad planning, player availability and load management in a