Golf Fitting Data Scientist & ML 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

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!