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 Manufacturing Analytics team develops data products, analytic software and provides insights to a broad range of skill teams and delivers value to Ford using critical thinking, artificial intelligence (AI), machine learning (ML), and optimization techniques.

As a Data Science Analyst, Complexity Analytics, 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 develop analytics products using your expertise in visualization, AI/ML, Statistics and Optimization using GDI&A approved packages and architectures. You will collaborate with Data Engineers and Software Engineers to develop robust analytics products. You will use your knowledge of the product driven operating model, analytic and software delivery via Google Cloud Platform to optimize the delivery of value. You will interact with business partners in Complexity to align with their needs and processes to ensure relevancy of products.

You'll have... 

Master’s degree in a quantitative field, such as Data Science, Engineering, Operations Research, Industrial Engineering, Statistics, Mathematics OR Computer Science 2+ year experience hands-on experience with mathematical programming, machine learning, artificial intelligence, optimization/simulation techniques, or statistical analysis Demonstrated technical skills in data analytics, AI/ML, operations research, and/or optimization 1+ year of experience delivering analytics solutions 1+ year experience with Agile team methodology

Even better, you may have...

PhD degree 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) Proven experience with developing data products/solutions to support analytic applications in Ford’s data ecosystem Experience with Product Driven Operating Model or Agile Product Development Process 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 Demonstrated hands on experience with deploying data products and/or analytic models in Ford’s on-prem and/or Google Cloud Platform Demonstrated experience to translate real-world business problems into analytical formulations and interpreting analytics results with non-analytics business partners Working knowledge of Manufacturing IT legacy systems such as FIS, Maximo, QLS, etc. Thorough understanding of the ‘Common Data Model’ standard published by Manufacturing

You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!

As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder…or all of the above? No matter what you choose, we offer a work life that works for you, including:

• Immediate medical, dental, vision and prescription drug coverage

• Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more

• Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more

• Vehicle discount program for employees and family members and management leases

• Tuition assistance

• Established and active employee resource groups

• Paid time off for individual and team community service

• A generous schedule of paid holidays, including the week between Christmas and New Year’s Day

• Paid time off and the option to purchase additional vacation time. 

For a detailed look at our benefits, click here: https://fordcareers.co/GSR-HTHD

This position is a range of salary grades 6-8.

Visa sponsorship is available for this position.

Candidates for positions with Ford Motor Company must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire.

We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status. In the United States, if you need a reasonable accommodation for the online application process due to a disability, please call 1-888-336-0660.

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What you'll be able to do:

Accelerate the application of value-added analytics and machine learning into the portfolio of products for Complexity Analytics. Drive analytic excellence into product teams by collaborating with Data Scientists, Data Engineers and Software Engineers in analytic and machine learning methods. Work closely with the Product Manager and Product Owner to translate Business Value needs into analytic deliverables and, where appropriate, software products for delivery by product teams. Work hands-on with the team and other partners to deliver solutions that meet our customer's requirements and needs. Act as a consultant to the business vs. an order taker. Balance "doing it right" with "speed to delivery" by identifying and mitigating risk, generating options, educating business and other decision makers, and taking on justified technical debt.