The Fitting Research Engineer will work within the Research department and be central to that mission, using data-driven methods and rigorous experimentation to move fitting from intuition to evidence.

In this role, you will develop, validate, and extend the analytical and software systems that help golfers find their optimal equipment. You will collaborate closely with engineering and development, product creation, tour staff, fitters, and technology teams to build solutions that are as practical in the field as they are sophisticated under the hood. The right candidate brings deep technical expertise, a bias toward action, and genuine enthusiasm for the game.

Essential Functions and Key Responsibilities:

• Build and own data pipelines that capture, clean, and structure large volumes of equipment and player performance data-including, but not limited to launch monitor outputs, biomechanical measurements, and physical club and ball properties
• Design and deploy machine learning models and recommendation systems that match players to equipment configurations optimized for their swing characteristics and performance goals
• Lead experimental studies that test hypotheses about equipment performance and player outcomes, applying rigorous statistical methods to generate reliable, actionable insights
• Develop internal tools, APIs, and mobile or web-facing applications that bring fitting intelligence to fitters, retail partners, and golfers directly
• Collaborate cross-functionally with R&D, product engineering, tour operations, and marketing to translate research findings into real-world product and fitting decisions
• Communicate findings clearly and compellingly to both technical and non-technical audiences through written reports, presentations, and interactive dashboards
• Stay current on advances in data science, machine learning, and sports analytics; identify and champion new approaches that improve fitting accuracy and efficiency
• Performs other related duties and assignments as required.

Knowledge and Skills Requirements:

Technical Expertise

• Strong foundation in statistical modeling, analytical experiment design, and hypothesis testing-comfortable moving from raw data to validated insight
• Practical knowledge and experience in physical experiment design and data collection
• Hands-on experience with machine learning frameworks and recommendation system architectures
• Proficiency in programming (i.e. Python, MATLAB) required; version control, and databases a plus
• Experience building and deploying software in production environments preferred
• Familiarity with or basic understanding of mechanical simulation / physics-based modeling

Interpersonal and Professional Skills

• Strong communicator who can translate complex analytical findings into clear, accessible language for diverse audiences
• Collaborative by nature-able to build trust and productive working relationships across research, development, engineering, information technology, and product creation teams
• Self-directed and intellectually curious: you ask good questions, pursue answers proactively, and bring solutions rather than just problems
• Organized and detail-oriented, with the ability to manage multiple workstreams in a fast-paced, competitive, and iterative environment
• Knowledge of golf-the game, the equipment, the fitting process, and even instruction-is strongly preferred and will meaningfully accelerate your impact in this role

Education, Work Experience, and Professional Certifications:

• B.S., M.S., or Ph.D. in Data Science, Computer Science, Statistics, Systems Engineering, or a related quantitative field
• B.S. with 3 - 5 years of relevant industry experience; M.S. with 1 - 2 years; or relevant PHD
• Prior experience in an industry setting with exposure to modern software development and deployment practices
• Experience with sports science, biomechanics, or consumer-facing recommendation systems is a meaningful differentiator

Work Environment / Physical Requirements:

• Primary office environment with significant computer use; occasional travel to test facilities, retail locations, or tour events may be required
• Ability to work flexible hours around project and event timelines as needed
• Light physical effort; occasional lifting or moving of lightweight materials (golf equipment, portable sensors, etc.)Frequent travel may be required.

TaylorMade is a performance driven organization and our total rewards approach to compensation is designed to support this. We consider many factors in determining base compensation, including position scope, job related knowledge, education, skills, experience, and work location. The expected annual base pay range for this position is $90,000 - $103,000. Additional benefits, such as health & wellness, performance bonuses, product discounts, holidays, paid time off, etc. may also be offered in accordance with our plans.

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