Senior Data Scientist
About The Position
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
Requirements
- 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
- 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
Nice To Haves
- Knowledge of Streamlit for building interactive data applications preferred
Responsibilities
- 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
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Number of Employees
5,001-10,000 employees
