Human Performance Data Specialist
Pubblicato il 13-08-2026 - Technogym in Emilia-Romagna
Our CompanyTechnogym inspires 70 million daily users to train using our innovative & engaging solutions for fitness, sport and health. By promoting the Healthness lifestyle of exercise, a balanced diet, and a positive mental approach, AI Tracking & Longevity, Technogym has rapidly grown into a success story of over 2,800 employees at 16 branches, expanding to more than 150 countries. It has been selected as Official Supplier to 10 editions of the Olympic Games - from Sydney 2000 to Milano Cortina 2026.Suppose you are a team player with strong relationship skills and an international approach, eager to invest your energy in building dreams. In that case, you have the right spirit to join Technogym because you have the IMBESTIO You will naturally fit our culture if you work out and live a healthy lifestyle, are proactive, determined, and are digitally savvy. Move with us for a better worldYour RoleWe are looking for a Human Performance Data Specialist to join our team at Technogym. The position will focus on the analysis and interpretation of complex data related to human performance,
with the goal of developing innovative training methodologies, personalized programs, and functional assessment protocols based on data and scientific evidence.Your ImpactAnalyze complex datasets derived from performance and training studies to extract meaningful insights and support evidence-based decision making.Develop predictive models and algorithms to optimize training protocols and assessment methodologies, leveraging advanced statistical techniques and machine learning approaches.Contribute to the definition of innovative methodologies based on data analysis and scientific literature, translating research findings into practical applications.Collaborate with engineering, marketing, and commercial teams to integrate analytical results into operational solutions and ensure data-driven product development.Prepare reports and presentations to share results with internal and external