Performance Data Scientist - First Team
Sporting Kansas City
Job Description Summary
The Human Performance (HP) Department is seeking a First-Team Performance Data Scientist to help the department accomplish their mission of creating a collaborative, data-informed staff committed to excellence by delivering holistic, player-centric health and performance. This is an exciting time to join the HP department committed to providing a culture where people thrive, and a platform that sets the standard for player health and performance in Major League Soccer. The First Team Performance Data Scientist will be tasked with connecting the first team sport science front end to SKC's centralized data analytics infrastructure. They will meet SKC's expectations of organized data collection, excellent data hygiene, consistent terminology, and the highest level of HIPPA compliance. The scope of data collected will comprehensively include all sport science and medical data in addition to data from auxiliary departments that are relevant to painting a clear holistic player-centric performance picture. They will work collaboratively with the HP department to make data accessible to staff and players. The data they provide will inform decisions regarding training periodization, athletic testing, player and positional profiling, athletic development, injury prevention, rehabilitation, and return to play protocols. They will be responsible for building the data models and analytics platforms that will be used to integrate all relevant performance data into daily, weekly, monthly, and seasonal reports to be used by the HP, technical, and recruiting departments to ensure the team's ability to consistently compete, ensure player safety, and to inform high-performance decisions. Job Description Essential Functions
The Human Performance (HP) Department is seeking a First-Team Performance Data Scientist to help the department accomplish their mission of creating a collaborative, data-informed staff committed to excellence by delivering holistic, player-centric health and performance. This is an exciting time to join the HP department committed to providing a culture where people thrive, and a platform that sets the standard for player health and performance in Major League Soccer. The First Team Performance Data Scientist will be tasked with connecting the first team sport science front end to SKC's centralized data analytics infrastructure. They will meet SKC's expectations of organized data collection, excellent data hygiene, consistent terminology, and the highest level of HIPPA compliance. The scope of data collected will comprehensively include all sport science and medical data in addition to data from auxiliary departments that are relevant to painting a clear holistic player-centric performance picture. They will work collaboratively with the HP department to make data accessible to staff and players. The data they provide will inform decisions regarding training periodization, athletic testing, player and positional profiling, athletic development, injury prevention, rehabilitation, and return to play protocols. They will be responsible for building the data models and analytics platforms that will be used to integrate all relevant performance data into daily, weekly, monthly, and seasonal reports to be used by the HP, technical, and recruiting departments to ensure the team's ability to consistently compete, ensure player safety, and to inform high-performance decisions. Job Description Essential Functions
- Oversee all peripheral First Team performance data science workflows, including the integration and maintenance of connections and pipelines within the club's central data infrastructure.
- o Training and match load
- o Readiness to train data, objective and subjective
- o Movement analysis
- o Strength, power, speed, agility and fitness
- o Medical
- o Diet and nutrition
- o Mental performance
- Ensure the highest level of data hygiene for all sports science data collection.
- Perform quality control on data sources, including GPS and athlete monitoring systems.
- Apply expertise in multiple programming and data-analysis languages to develop analytical models that evaluate the effectiveness of training periodization strategies and forecast the impact of future microcycles.
- Build tools for HP department staff to increase the precision of workflows and training plans.
- Create usable dashboards that paint a clear picture of player readiness.
- Deliver actionable, high-resolution insights that enable the HP department to optimize marginal gains across all areas of performance.
- Lead and leverage sport science interns to maximize data science efficiency and grow the department.
- Provide insights into workload trends, performance benchmarks, return-to-play indicators, and training optimization.
- Communicate real-time training and match analytics to performance staff to inform substitutions and support live decision-making.
- Collaborate with the broader data analytics team to connect relevant data from sports science, technical analysis and recruiting to create a holistic view of each player.
- Use sports science to collaboratively create player and positional profiling.
- Manage all aspects of the HP departments AMS systems.
- On occasion, attend/participate in activities/meetings/programs as required by MLS.
- Curious, energetic, and highly collaborative.
- Naturally player-centric and highly accountable.
- Must be collaborative, team-oriented, with confidence and professionalism to address behaviors that may compromise team culture or SKC standards.
- Empathetic and emotionally intelligent, with a proven ability to foster trust, psychological safety, and strong interpersonal relationships.
- Exceptional communicator who navigates challenging conversations with honesty, professionalism, and respect, both in giving and receiving feedback.
- Strong written and verbal communication skills, detail-oriented and organized with the ability to simultaneously handle multiple tasks and adapt to change.
- Composed, driven and adaptable, capable of thriving in a dynamic, high-performance team environment.
- Professional integrity, discretion, and commitment to the club's values and player-development philosophy.
- Detail-oriented with the ability to think ahead and proactively, collaboratively, solve problems.
- Minimum of 5 years of experience in a sports environment, preferably with soccer, at an elite level (collegiate, professional, Olympic).
- Strong understanding and familiarity of MLS preferred.
- Master's degree or higher in Sports Science, Data Science, or a related field.
- Knowledge of, and experience in, utilizing sports science technologies (e.g., GPS, Optical Tracking, Internal Load Monitoring, VALD, Force Plates, Physiologic Testing, Strength/Power Testing Equipment, and current Athlete Monitoring System (AMS) platforms.
- Must be an expert in various data languages (R, Python, Shiny Apps, Tableau, Power BI, Excel, etc.)
- Must be skilled in building models and platforms that can create the answers to the club's performance questions.
- High level of comfort with all major AMS systems (Kitman Labs, SmartaBase, etc.)
- Highly knowledgeable in data security.
- Certified Performance Sports Scientist (CPSS) certification by NSCA (National Strength and Conditioning Association).
- HIPAA Compliant Course and Health Information Certification.
- Based primarily at the Club's training facility and stadium, with potential regular travel for matches and events.
- Must be able to lift and carry up to 100 pounds routinely as a part of session set up, breakdown and demonstration.
- Ability to work in indoor and outdoor environments under varying weather conditions.
- Ability to work non-traditional hours, including evenings, weekends, travel, and extended days.
- We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, age, disability, gender identity, marital or veteran status, or any other protected class.
Vacancy posted 9 hours ago
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