Data Scientist - MADE Operations

New Balance

119d

About The Position

The MADE Operations Data Scientist will enable a more data-driven, digitally native culture across the MADE in USA team by applying advanced analytics, statistical modeling, and data science techniques to solve operational challenges. This role supports cross-functional operations—spanning product development, engineering, planning, purchasing, and logistics—by delivering actionable insights, leading metric development, and building predictive models and alerting systems. The ideal candidate combines technical excellence in data science and data engineering with a deep understanding of footwear and apparel manufacturing, and the ability to translate complex data into clear, impactful business decisions.

Requirements

• Minimum 2 years of experience in a data analytics or data science role within a brand that manufactures apparel and/or footwear.
• Proficiency in Python and open-source data science tools (e.g., Pandas, NumPy, Scikit-learn, Jupyter).
• Strong experience with Power BI, including DAX, data modeling, and dashboard design.
• Familiarity with manufacturing, supply chain, or product development data and systems.
• Experience designing semantic layers and integrating data from multiple sources (e.g., ERP, MES, PLM).

Responsibilities

• Develop and maintain Power BI dashboards and reporting systems that surface key operational metrics and drive visibility across the MADE organization.
• Build and deploy analytical models to forecast performance, identify bottlenecks, and optimize processes across product development, manufacturing, planning, and logistics.
• Design and maintain semantic data models that enable scalable, self-service analytics and support advanced querying and analysis.
• Conduct exploratory data analysis (EDA) to uncover trends, anomalies, and opportunities for operational improvement.
• Collaborate with cross-functional stakeholders to frame business problems as data science questions and deliver actionable insights.
• Implement alerting and monitoring systems that proactively flag deviations in performance or quality metrics.
• Partner with IT and data engineering teams to ensure robust data pipelines and infrastructure that support modeling and reporting needs.
• Validate and improve data quality across systems such as ERP, MES, PLM, and other operational platforms.

Benefits

• Comprehensive traditional benefits package including three options for medical insurance, dental, vision, life insurance, and 401K.
• Opportunities for online learning and development courses, tuition reimbursement, and $100 monthly student loan support.
• Yearly $1,000 lifestyle reimbursement, 4 weeks of vacation, 12 holidays, and generous parental leave.
• Flexible work schedule with a hybrid model encouraging in-person teamwork and collaboration.
• Work from Anywhere (WFA) for four weeks per calendar year.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level