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Ford Motor Company

Job Description
Job Title: Econometrician

Position Overview/Description:
Ford Motor Company's Global Data, Insight, and Analytics (GDI&A) organization is looking for a motivated and talented Econometrician to lead various projects that involve all phases of econometric/optimization model development, evaluation, and deployment. You will have the opportunity to work with some of the brightest global subject matter experts that are transforming the automobile industry. In this role you will create cutting edge models, evaluate and monitor model performance, and perform benchmarking with the goal of maintaining and exceeding the highest levels of accuracy and competitiveness.

  • Lead the development of market demand models to support scenario analysis for pricing, volume, product and technology development with the consideration of macro environment, feature and technology choice, regulatory compliance, and investment
  • Lead the development of tracking methodologies and reports to monitor model accuracy and evaluate performance, preparing analysis to back-test and compare competing modeling methodologies, model maintenance and enhancements
  • Utilize structural models to simulate business performance over different competitive and economic scenarios
  • Utilize optimization software to evaluate pricing methodologies
  • Use data mining techniques to find opportunities within the pricing area
  • Work with various data sources and platforms (Web, PC, Mainframe, Unix/Linux, Teradata) to gather data
  • Execute both descriptive and inferential ad hoc requests in a timely manner

Job Requirements:

Basic Qualifications:
  • Master’s Degree in Economics or other quantitative areas, such as Physics, Math, Statistics, Computer Sciences
  • 2+ years of experience conducting complex statistical analysis in a business or academic environment
  • 2+ years of experience in one or more of the following:
    • Models with limited dependent variables (e.g. choice models, selection models)
    • Large scale data manipulation and mining/pattern recognition
    • Monte Carlo simulation and other simulation techniques
    • Optimization techniques (e.g. linear/nonlinear/dynamic programming)
    • SAS programming
Preferred Qualifications:
  • PhD in Economics or other quantitative areas, such as Physics, Math, Statistics, Computer Sciences
  • Experience with parallel/grid computing, and programming in a variety of software platforms
  • Knowledge of theoretical/empirical techniques commonly used in industrial organizations (e.g. game theory, contract theory, oligopoly theory)
  • Experience converting business problems into analytics formulations, then interpreting the analytics results and translating them into easily understood products for all levels of business customers
  • SQL programming experience
  • Proficiency in SAS is a definite plus
  • Ability to drive results and handle multiple projects within a given timeframe.
  • Strong oral and written communication and people skills
  • Demonstrated track record of project development, management, and implementation
  • Inquisitive, proactive and interested in learning
  • Well-organized, independent and ready to work with minimal supervision

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.

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.