Principal Supply Chain Data Scientist Full-time

Principal Supply Chain Data Scientist

Considered the founder of the industry, Genentech, now a member of the Roche Group, has been delivering on the promise of biotechnology for more than 45 years.

Genentech is a biotechnology company dedicated to pursuing groundbreaking science to discover and develop medicines for people with serious and life-threatening diseases. Our transformational discoveries include the first targeted antibody for cancer and the first medicine for primary progressive multiple sclerosis.

We celebrate our unique history as the pioneers of scientific breakthroughs that have an incredible track record of improving lives. And yet, our ambitions are bigger and bolder. Together, we are united in a bold quest to solve the world's most complex health challenges and serve society.

Our ability to bring transformative medicines to patients depends on the positive experience, engagement and resilience of everyone who works here. Our employees are the heart of Genentech and the driving force behind the progress that brings important new medicines to the people who need them. We believe a great people experience is critical for revolutionizing healthcare and that's why we're committed to cultivating an environment where people feel valued, included and able to thrive.

The Opportunity

As the Principal Supply Chain Data Scientist, you will lead advanced analytical initiatives to optimize pharmaceutical distribution processes, leveraging cutting-edge data science methodologies and technologies. Based at our main US Distribution facility in Louisville, Kentucky, this role goes beyond traditional data analysis to design predictive and prescriptive models, fostering innovation in supply chain strategy and decision-making. Reporting directly to the Head of Business Excellence, you will drive advanced analytics, process optimization, and strategic supply chain insights. This position combines technical expertise, leadership, and collaboration to impact the broader supply chain ecosystem.

What You'll Do

Advanced Data Analysis & Predictive Modeling:

• Design, implement, and validate advanced algorithms and predictive models to solve supply chain challenges in a high-pace distribution operation.
• Apply machine learning, statistical methods, and optimization techniques to enhance forecasting, inventory management, and logistics planning.
• Analyze large datasets and business systems to identify trends, patterns, and innovative opportunities using data mining tools and statistical approaches.
• Develop advanced AI-driven tools for improved planning accuracy, distribution efficiency, and warehouse operations.
• Develop and maintain reports and dashboards using Tableau.
• Generate and distribute reports using SQL Reporting Services.

Supply Chain Distribution Optimization & Innovation:

• Develop and implement distribution plans to optimize product movement from manufacturing facilities to customers.
• Create and execute detailed schedules for deliveries, warehouse operations, and related activities.
• Effectively manage warehouse capacity modeling and assessments to ensure accurate and timely insights.
• Conduct space utilization analysis, evaluating how effectively warehouse space is being used and identifying areas for improvement.
• Plan inbound/outbound logistics to meet daily and weekly distribution schedules.
• Plan efficient delivery routes and schedules for cost-effective transportation of medications.
• Analyze the distribution network to identify bottlenecks, optimize routes, and improve overall efficiency and cost-effectiveness.
• Drive the creation of digital twin models for scenario planning and strategic decision-making, ensuring efficient and sustainable supply chain practices.
• Evaluate and propose innovation opportunities through investment modeling and process improvements.

Strategic Impact & Communication:

• Serve as a strategic advisor, translating business challenges into actionable, data-driven insights.
• Present findings, recommendations, and strategic plans to senior leadership, aligning advanced analytics with organizational goals.
• Act as the subject matter expert in supply chain analytics, providing guidance across initiatives and projects.
• Manage data governance frameworks, ensuring integrity, accuracy, and compliance with regulations.

Performance Monitoring, Accurate Reporting, Improvement, and Problem Solving:

• Track key performance indicators (KPIs) such as on-time delivery rates, inventory turns, and order fulfillment rates to identify areas for improvement.
• Analyze performance data to identify issues and implement changes to enhance efficiency and customer service.
• Address disruptions in the distribution process promptly and develop contingency plans for potential risks.
• Regularly review performance metrics and adjust processes for ongoing optimization.
• Use advanced planning systems and AI-driven tools to improve planning accuracy and optimize warehouse operations.
• Create comprehensive documentation and reports to communicate insights and recommendations.

Regulatory Compliance:

• Ensure compliance with relevant regulations and guidelines related to pharmaceutical distribution and supply chain management.

Business Intelligence (BI):

• Create, implement, and manage data integration workflows using SQL Integration Services.
• Develop multidimensional cubes and tabular models in SQL Analysis Services.
• Ensure data integrity, accuracy, and security across all BI systems.
• Continuously improve BI processes and methodologies to enhance efficiency and effectiveness.

Who You Are

• Bachelor's degree in a quantitative or technical field (e.g., Data Science, Supply Chain Management, Logistics, Operations Research, Mathematics, or Computer Science) required.
• Advanced degrees (Master's, PhD) in the same fields strongly preferred, with demonstrated expertise in supply chain analytics.
• Over 10 years of experience in supply chain analytics, business intelligence, or advanced data science roles, with a minimum of 8 years in advanced supply chain analytics.
• Demonstrated track record of implementing analytics within a supply chain context, with pharmaceutical distribution expertise strongly preferred.
• Proficiency in Python, SQL, and cloud-based tools with experience in developing machine learning models and optimization algorithms.
• Hands-on experience with advanced statistical and machine learning packages (e.g., scikit-learn, TensorFlow, R).
• Skilled in optimization tools (e.g., Gurobi, CPLEX) and inventory management platforms.
• Deep understanding of supply chain management principles, including forecasting, inventory optimization, logistics planning, and procurement.
• In-depth experience with pharmaceutical distribution requirements, industry standards, and compliance regulations.
• Familiarity with warehouse operations, capacity planning, network design, and space utilization analysis.
• Familiarity with SQL Integration Services, SQL Analysis Services, and SQL Reporting Services.

Relocation funding is not available for this role.

The expected salary range for this position based on the primary location of Louisville, Kentucky is $127,100 – $236,100. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.

Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.

If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form.