At Ford’s Data & Analytics organization, we like data - a lot. We are looking for smart, nice, and curious people like you people who “get” data, thrive in a fast-paced environment, and have wicked analytic and data science skills. We are looking for people who can combine an inherent curiosity for data & analytic techniques with the right business savvy to transform data into insight so we can help Ford Motor Company make smarter decisions.
We are currently looking for talented and motivated individuals to work on supply chain & optimal sourcing problems. This is an exciting opportunity to join Ford Motor Company's Global Data, Insight, and Analytics (GDIA) organization and apply the latest tools and methods in Statistics, Big Data, and Data Science to a variety of business problems. In this role you will be supporting Ford's Procurement Organization and developing approaches that optimize their $100+B spend. You will collaborate with partners in product development, manufacturing, purchasing, warranty, material planning, logistics and other Ford activities to define problems, identify data, develop predictive & prescriptive models and deliver optimization solutions.
You will have the opportunity to work with some of the best and brightest in the field and be at the forefront of the data science movement that is transforming the automotive industry.
Responsibilities:
Support the development and delivery of analytic models using skills such as data acquisition and management, algorithm design, and model development & refinement
Acquire deep understanding of the business problems and translate them into appropriate mathematical representations
Encode mathematical abstractions into prototype computer programs or models
Ensure overall quality of the data & solutions throughout the analytic development process
Interpret results and communicate them to technical and non-technical audiences, cross-functional teams and executive leadership
Job Requirements
Basic Qualifications:
Master’s Degree
3+ years of experience with data mining OR statistical analysis
1+ year of experience applying operations research, mathematics, AND/OR statistics approaches to business problems (professional, academic and/or internships)
Preferred Qualifications:
PhD preferred. Prefer graduate degree/PhD in statistics, operations research, mathematics, computer science, econometrics, industrial engineering or related quantitative fields
Mathematical programming and optimization techniques
Proficiency in analytic languages and frameworks such as Python, SAS, R, CPLEX, MATLAB, or Java
Proficiency in database query and management tools (SQL, Alteryx, etc.)
Past experience and knowledge in automotive industry highly desired
Project management experience and strong leadership skills such as business acumen and strategic vision a big plus
Comfortable working in an environment where problems are not always well-defined
Inquisitive, proactive, and interested in learning new tools and techniques
Strong oral, written and interpersonal communication skills
Well-organized, independent and ready to work with minimal supervision
Have a desire to excel and work with talented people
The distance between imagination and … creation. It can be measured in years of innovation, or in moments of brilliance. When you join the Ford team discover all the benefits, rewards and development opportunities you’d expect from a diverse global leader. You’ll become part of a team that is already leading the way, with ingenious solutions and attainable products – and it is always ready to go further.
Candidates for positions with Ford Motor Company must be legally authorized to work in the United States on a permanent basis. Verification of employment eligibility will be required at the time of hire. Visa sponsorship is not available for this position, TN visa holders may be considered.
Ford Motor Company is 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