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DuPont
Digital Acceleration Leader - Analytical & Decision Sciences
Career Insights for Data Science Manager
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What they do
A Data Science Manager manages a team of data scientists, machine learning engineers and big data specialists. They lead data mining and collection procedures, ensure data quality and integrity, build analytic systems and predictive models, and test the performance of data science products.
$139,637 / year median in Delaware
+16% projected growth
Job Description
Opened Recently Job Type Experienced Postal Code 19805 Wilmington, Delaware Job Id 249866W Category Science & Technology Posted On - 08/13/2026 Job available in 2 locations Wilmington, Delaware, United States of America Midland, Michigan, United States of America At DuPont, our purpose is to empower the world with essential innovations to thrive. We work on things that matter. Whether it's providing clean water to more than a billion people on the planet, producing materials that are essential in everyday technology devices from smartphones to electric vehicles, or protecting workers around the world. Discover the many reasons the world's most talented people are choosing to work at DuPont. Why Join Us | DuPont Careers At DuPont, we are accelerating innovation by transforming measurement science into structured, decision-ready data. The Analytical & Decision Sciences (ADS) Digital Acceleration Leader will play a key role in advancing how DuPont leverages connected laboratory data, digital technologies, and AI/ML capabilities to drive innovation across R&D, Application Development, Manufacturing Technology, and Product Stewardship & Regulatory organizations. This role is ideal for a hands-on scientific and digital leader with a proven ability to translate complex scientific data into actionable insights. The successful candidate will help establish the standards, workflows, and digital pathways needed to convert analytical and measurement science data into reusable, structured information within existing digital platforms, and apply that information to solve critical business and technical challenges. Working closely with ADS, business innovation teams, and Information Technology (IT), this leader will accelerate project delivery, improve decision-making, and unlock greater value from both current and historical scientific data. Success in this role requires a combination of strategic vision, technical expertise, practical implementation experience, and the ability to influence across a highly matrixed organization. The individual will also help build organizational capability by advancing data-enabled measurement science and driving adoption of scalable, interoperable, and automated ways of working. Responsibilities Develop and implement pathways that convert measurement science data into structured, reusable information within LIMS and other digital platforms to support innovation. Lead the integration of laboratory measurements from ADS and business laboratories into connected digital systems, including the capture and utilization of historical data. Partner with R&D, Application Development, Manufacturing Technology, and Product Stewardship & Regulatory teams to identify opportunities where structured data can accelerate the development of products, formulations, processes, and technical solutions. Navigate complex technical and organizational challenges, identify practical solutions, and drive implementation through influence and collaboration. Advance automation across measurement science workflows, including method development, data acquisition, analysis, interpretation, and reporting. Apply data mining, data science, and digital technologies to extract value from current and historical scientific information. Establish data standards and improve data fluency across laboratories, sites, and businesses to enable scalable and reusable solutions. Collaborate with IT, digital teams, and laboratory automation resources to evaluate, pilot, and deploy tools that connect scientific workflows with enterprise digital capabilities. Provide hands-on leadership through coaching, training, project engagement, and knowledge-sharing forums that build digital and data capabilities across the organization. Qualifications Bachelor's degree in Chemistry, Chemical Engineering, Materials Science, Data Science, Computer Science, Engineering, or a related technical field; Advanced degree preferred. Demonstrated success translating digital capabilities, data science, automation, and structured data insights into impactful solutions for innovation, manufacturing, and customer-facing technical challenges Experience with