In Global Data Insight & Analytics (GDIA), we aspire to navigate Ford Motor Company through the disruptiveness of the information age, harnessing the power of data and artificial intelligence to realize the enterprise’s known goals, reveal hidden opportunities, and achieve data superiority.The GDIA Strategy & Enterprise Analytics (SEA) team develops data analytics products and provides insights to a broad range of skill teams and delivers the most value to Ford using critical thinking, artificial intelligent (AI), machine learning (ML), and optimization techniques.

As the Data Science Specialist, Enterprise Risk Analytics, you will primarily partner with the Office of the General Counsel (OGC) and other cross-functional teams to understand their top priorities. You will use your knowledge of data and advanced analytics to identify and articulate the role data and analytics products play in helping the business achieve their goals. You will communicate high level roadmaps with key stakeholders and work to ensure GDI&A team has the necessary support to deliver business value. You will work internally to ensure your team has a clear understanding of the priorities. You will support your team as they prioritize the research, development, and delivery of relevant products. You will use your knowledge of the product driven operating model, analytic and software delivery via Google Cloud Platform to optimize the value delivery.

Dearborn, MI, United States

Basic Requirements

• Master’s degree quantitative field, such as Data Science, Engineering, Operations Research, Industrial Engineering, Statistics, Mathematics, Computer Science, or related field
• 1+ year of demonstrated technical skills in data analytics, AI/ML, operations research, and/or optimization
• 1+ year of proven experience with developing data products/solutions to support analytic applications in Ford’s data ecosystem
• 1+ year of experience with Product Driven Operating Model or Agile Product Development Process
• 1+ year proven proficiency in developing and deploying analytic models, working in a team environment, supporting customers and/or end users
• Comfortable working in an environment where problems are not always well-defined
• Strong interpersonal and leadership skills, with ability to communicate complex topics to leaders and peers in a simple and clear manner
• Well-organized, independent, and ready to work with minimal supervision
• Inquisitive, proactive, and interested in learning new tools and techniques

Preferred Qualifications:

• PhD. is preferred in quantitative field, such as Data Science, Engineering, Operations Research, Industrial Engineering, Statistics, Mathematics, Computer Science, or related field
• Knowledge and experience working with OGC and related teams/activities (e.g., Compliance, Litigation and Regulatory)
• 3+ year experience hands-on experience with mathematical programming, machine learning, artificial intelligence, optimization/simulation techniques, or statistical analysis
• 1+ year demonstrated hands on experience with deploying data products and/or analytic models in Ford’s on-prem and/or Google Cloud Platform
• 1+ year of experience leading an analytic team
• 1+ year experience with Agile team methodology
• Demonstrated experience to translate real-world business problems into analytical formulations and interpreting analytics results with non-analytics business partners

Responsibilities

Position Responsibilities:

• Lead a team of data scientists and collaborate with others to meet data and analytics needs for Ford’s customers and/or internal business partners
• Collaborate with business partners to understand the business opportunities and translate high-level ideas into well-defined analytics strategy and roadmap
• Leverage experience and domain knowledge to help identify and define data analytics opportunities in relevant to OGC and related teams/activities, e.g., Compliance, Litigation and Regulatory
• Develop and manage related data and analytics demands, determine how to allocate work across team and skill sets to deliver solutions, perform ad-hoc studies, ensure on-time delivery, and quantify project benefits
• Provide technical guidance on solution techniques and best practices; Create option set to solve problems while balancing desirability, feasibility, and viability tradeoffs
• Leverage knowledge of analytic development and deployment to oversee end-to-end development of product solutions to ensure iteratively develop quick, customer centric solutions aimed at uncovering the real business value
• Author Objectives and Key Results (OKRs) and Point of View Paper
• Support talent acquisition, engagement, and retention; Promote an engaged, diverse & inclusive global team with exciting work and rewarding careers