Fitting Research Engineer

TaylorMade Golf; Carlsbad (CA); On-site; USD 90,000 - 103,000; Full time

Benefits offered by this job

Health & wellness benefits

Performance bonuses

Product discounts

Paid time off

Job summary

TaylorMade Golf is seeking a Data Scientist to develop data pipelines and machine learning models that enhance equipment fitting for golfers. This role involves collaborating with various teams to translate research findings into actionable insights.

The ideal candidate possesses a strong background in statistical modeling and machine learning, alongside a passion for golf. Competitive compensation along with beneficial perks are included. If you have innovative ideas and are eager to impact the world of sports analytics, we want to hear from you!

Qualifications

• Strong foundation in statistical modeling and hypothesis testing.
• Hands-on experience with machine learning frameworks.
• Experience in physical experiment design and data collection.
• Ability to manage multiple workstreams and communicate findings clearly.

Responsibilities

• Build data pipelines for performance data.
• Design machine learning models to optimize equipment.
• Lead experimental studies on equipment performance.
• Collaborate with R & D and marketing teams.

Skills

Statistical modeling

Machine learning frameworks

Programming (Python, MATLAB)

Data analysis

Collaboration skills

Knowledge of golf

Education

B.S./M.S./Ph.D. in Data Science, Computer Science, or Statistics

Tools

Version control

Database management

Job description

Key Responsibilities

• Build and own data pipelines that capture, clean, and structure large volumes of equipment and player performance data—including 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.
• Perform 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 (Python, MATLAB); version control and database experience 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: 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 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 Ph.D.
• 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.

Compensation and Benefits

• Expected annual base pay range: $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.

Equal Employment Opportunity

TaylorMade Golf Company is an equal opportunity employer. All qualified applicants receive consideration for employment without regard to race, religious creed, color, national origin or ancestry, physical or mental disability, medical condition, genetic information, marital status, sex, pregnancy, gender, gender identity, gender expression, age, sexual orientation, military and veteran status or any other basis protected by federal, state or local law, ordinance, or regulation.