Senior Data Scientist

Job Description
Reports to: VP Data & Analytics
As a Senior Data Scientist, You Will

• Partner with business leaders to identify high-value opportunities in areas such as demand planning, capacity/production planning, procurement, and financial forecasting
• Develop a firm understanding of specific business processes and real-world workflows
• Work closely with cross-functional teams including domain experts, business analysts, data engineers and software engineers
• Lead data science initiatives that impact operations globally across multiple business units
• Define project scope, timelines and deliverables in collaboration with business leaders
• Architect scalable machine learning and forecasting solutions within cloud platforms such as AWS, Azure, Databricks, and Snowflake
• Ensure models are production-ready, robust, and maintainable with appropriate monitoring and retraining pipelines
• Develop standardized methodologies and frameworks to ensure scalability and consistency across diverse environments
• Ensure compliance with data governance, privacy, and security standards while scaling analytics solutions globally
• Manage and mentor interns, junior data scientists and analysts
• Translate advanced analytics results into strategic recommendations for VP and C-level leadership
• Utilize programming languages such as SQL, Python for data manipulation, analysis and model development

Suggested Qualifications

• Master’s degree in a quantitative discipline
• Five or more years of professional data science experience in manufacturing and/or supply chain environments
• Hands-on experience working with ERP data and operational processes including order-to-cash, procure-to-pay, and demand-to-deliver
• Proven ability to communicate complex or technical concepts clearly to both technical and non-technical audiences
• Advanced proficiency in Python, SQL and PySpark; experience wrangling large relational datasets
• Deep expertise in machine learning, forecasting and optimization
• Experience deploying enterprise-scale solutions in cloud environments (AWS experience preferred)
• Proficient in at least one data visualization library such as Matplotlib, Seaborn, or Plotly
• Knowledge of Streamlit for building interactive data applications preferred
• Familiarity with MLOps practices, CI/CD pipelines, and model lifecycle management
• Demonstrated ability to drive business impact and ROI through analytics
• Strong track record of executive-level communication and influence
• Experience leading cross-functional teams across multiple geographies