Engineer Fitting Logic

TaylorMade Golf Company•Carlsbad, CA

4d•$90,000 - $103,000•Onsite

About The Position

Golf fitting sits at the intersection of performance science and personalization—and TaylorMade is committed to continue pushing and advancing that intersection into a competitive advantage. 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.

Requirements

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
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
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

Nice To Haves

Experience building and deploying software in production environments preferred
Familiarity with or basic understanding of mechanical simulation / physics-based modeling
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
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

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.