Associate Data Scientist On site

Callaway Golf is the leading manufacturer of premium golf clubs, balls, performance gear and accessories worldwide. Through an unwavering commitment to innovation, we push the limits of performance and create demonstrably superior products designed to make every golfer a better golfer.

Our company is a blend of experience and diverse backgrounds, and together we look to move the game forward, and we want top-notch people to join us in that mission!

By joining Callaway Golf, you also join part of the portfolio of brands within Topgolf Callaway Brands, an unrivaled tech-enabled Modern Golf and active lifestyle company delivering leading golf equipment, apparel, and entertainment, with a portfolio of global brands including Topgolf, Callaway Golf, TravisMathew, Toptracer, Odyssey, OGIO, Jack Wolfskin, and World Golf Tour (“WGT”). “Modern Golf” is the dynamic and inclusive ecosystem that includes both on-course and off-course golf.

Are you passionate about turning raw data into real-world impact? Callaway Golf is looking for an Associate Data Scientist to join our team at the Chicopee golf ball manufacturing facility—an environment where innovation meets precision. This is a unique opportunity to apply your data science skills directly to manufacturing and supply chain operations, working side-by-side with engineers to solve complex technical challenges, optimize processes, and drive efficiency. We’re looking for someone who not only brings solid experience in Python, SQL, and machine learning fundamentals, but also has an engineering mindset—ideally with a background in mechanical, chemical, or a related field. You’ll build machine learning models, design data pipelines, and deliver insights that shape how our products are made. If you have 1–2 years of experience and the interpersonal agility to thrive in a fast-paced, direct, and collaborative environment—this is your shot.

Key Responsibilities:
- Analyze and interpret large data sets related to manufacturing and supply chain operations to identify trends, patterns, and opportunities for improvement
- Develop statistical models and machine learning algorithms to optimize manufacturing and supply chain processes, reduce costs, and improve efficiency
- Collaborate with cross-functional teams to identify business needs, design experiments, and develop solutions that leverage data analytics and machine learning techniques
- Create and maintain data pipelines and databases to support ongoing data analysis and modeling activities
- Communicate findings and insights to key stakeholders in a clear and concise manner
- Continuously monitor and evaluate model performance to ensure accuracy, efficiency, and effectiveness

Requirements:
- Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering or a related field
- 1+ years of experience working in a data science role, preferably in a manufacturing or supply chain environment
- Strong proficiency in programming languages such as Python or R
- Proficiency in Azure, Snowflake and Airflow
- Expertise in statistical modeling, machine learning, and data visualization techniques
- Experience with database technologies such as SQL and NoSQL
- Familiarity with manufacturing and supply chain processes and systems
- Excellent communication skills and ability to work collaboratively in a cross-functional team environment
- 20% travel required

Technical Skills:
- Proficiency in programming languages such as Python or R for data manipulation, analysis, and modeling using libraries like NumPy, Pandas, and SciPy
- Expertise in statistical modeling and machine learning including regression, time series forecasting, clustering, classification, and deep learning applied to manufacturing and supply chain problems
- Ability to create insightful visualizations using Matplotlib, Seaborn, or Power BI
- Experience working with SQL and NoSQL databases, including schema design and query optimization
- Strong understanding of manufacturing and supply chain processes including procurement, production, logistics, and distribution