Data Products Finance Lead

Responsibilities

• Lead & Develop a High-Performing Team:
  Supervise, mentor, and grow a team of finance and data analysts. Foster a culture of collaboration, innovation, and continuous improvement.
• Drive Data Product Strategy & Delivery:
  Oversee the end-to-end lifecycle of data products, from ideation and requirements gathering with stakeholders in Engineering and Finance to development, deployment, and performance monitoring.
• Deliver Material Cost Reduction Insights:
  Guide your team in analyzing complex datasets (e.g., bill-of-materials, supplier quotes, engineering specifications) to identify and quantify opportunities for material cost savings and waste reduction.
• Enhance Engineering & Capital Efficiency:
  Develop analytical frameworks and data models to measure and improve engineering process efficiency, resource allocation, and the ROI of capital expenditures.
• Serve as a Cross-Functional Partner:
  Act as the primary liaison between Product Development Finance, Engineering, IT, and Procurement. Translate business needs into technical requirements and communicate complex analytical findings to senior leadership in a clear, concise manner.
• Champion Data-Driven Decision Making:
  Promote the strategic use of data and analytics throughout the product development process, ensuring that financial decisions are supported by robust, data-backed insights.
• Innovate and Improve:
  Stay current with the latest trends in data analytics, business intelligence, and financial modeling to continuously enhance the team’s capabilities and the sophistication of our data products.

• Bachelor’s degree in Finance, Economics, Data Science, Computer Science, Engineering, or a related quantitative field.
• 5 years of experience in a role involving financial analysis, business intelligence, or data analytics.
• 2 years of experience in a formal or informal leadership capacity (e.g., team lead, project manager, or direct supervisor).
• Strong understanding of financial principles, including cost accounting, budgeting, forecasting, and capital investment analysis.
• Proven experience working with large, complex datasets and proficiency with data analysis tools such as SQL, Python (with libraries like Pandas, Num Py), or R.
• Demonstrated experience with data visualization platforms like Tableau, Power BI, or Qlik for creating impactful dashboards and reports.
• Excellent communication and storytelling skills, with the ability to present complex information to both technical and non-technical audiences.
• Master’s degree (MBA, MS in Finance, Data Science, or Analytics).
• Experience with in the automotive, manufacturing, or heavy industry sectors.
• Direct experience with product development finance, vehicle cost engineering, or program finance.
• Familiarity with automotive product development processes and cost structures.
• Experience applying advanced analytics, statistical modeling, or machine learning techniques to solve business problems.
• Proven track record of managing cross-functional projects and delivering results in a large, matrixed organization.

Ford