Data Scientist- Operational Excellence

Data Scientist- Operational Excellence

About the job

The Role And Responsibilities

In this role you will drive a wide variety of data science projects that will focus on providing senior leadership with the metrics they need to make strategic and tactical decisions. The metrics will need to be timely and provide guidance on where decisions need to be made. This will require harmonizing KPIs (Key Performance Indicators) across various businesses. This role will touch on metrics and analysis ranging from supply chain & manufacturing (e.g. Delivery to Promise, Total Cost of Maintenance, COGs (Cost of Goods Sold)) to finance & capital (Net Working Capital Turns, Inventory Days of Supply, etc). You will work collaboratively with business and technical partners to rapidly advance projects from ambiguously-defined ideas to value-creating solutions in production. The ideal candidate will be highly versatile and willing to take on different roles as required to deliver a solution, including exploratory data analysis, data mining, data cleaning, and communication of results. The ideal candidate will be focused on achieving business objectives through data science, willing to pivot quickly from dead ends, and have strong collaboration & communication capabilities with non-technical business colleagues.

Your Key Responsibilities

  • Develop, harmonize and define corporate KPIs to help leaders make strategic decisions based on current business environments
  • Execute the POC for the corporate level metrics vision
  • Develop Community of Practice (CoP) for data scientists in DuPont
    • Includes starting up, organizing and networking the CoP for data scientists in DuPont
  • Develop Knowledge in SAP and the data it contains
  • Identify other data sources as needed and how to get that data into the data lake as needed
  • Ensure security and leveragability of data used for digital products across company
  • Introduce new technologies / tools in data science to improve efficiency and advance digital transformation throughout all Businesses / Functions
  • Collaborate and foster strong relationships with Business / Function stakeholders to leverage existing data and drive digital acceleration at scale
  • Utilize agile to deliver innovative solutions and manage 3rd party data engineers as needed

Your Qualification Profile

  • BS/MS Degree in applied mathematics, data science, computer science, or related field
  • 5-10+ years of relevant work experience in a data science role
  • Expertise of data modeling and structures
  • Experience using Microsoft Azure service platforms (e.g. Databricks, MLflow, etc)
  • Experience with manufacturing use cases such as process optimization and predictive maintenance
  • Experience with supply chain use cases such as inventory management, and supply chain optimization
  • Knowledge of querying languages, with expertise in at least 1 (e.g. SQL)
  • Experience with data visualization tools (e.g. Power BI)
  • Demonstrated understanding and experience with agile methodologies
  • Strong communication experience with multi-disciplinary teams
  • Must have the ability to apply intellect, creativity, adaptability, judgement and management skills to achieve required results.
  • Collection and aggregation of data
  • Data modeling and architecture design / implementation
  • Cross-disciplinary team collaboration
  • Written and verbal communication skills

Implementation Guidance

This role will report to the OpEx Data and Metrics Leader

DuPont is an equal opportunity employer. Qualified applicants will be considered without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, veteran status, disability or any other protected class. If you need a reasonable accommodation to search or apply for a position, please visit our Accessibility Page for Contact Information.

For US Applicants: See the “Equal Employment Opportunity is the Law” poster at: http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf

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