FAQs
What is the mission of the Global Data Insight & Analytics team at Ford Motor Company?
The mission of the Global Data Insight & Analytics team is to enable Ford to clearly see business conditions, customer needs, and the competitive landscape through the intelligent use of data, metrics, and analytics, driving evidence-based decision-making.
What qualifications are required for the Data Scientist position?
Candidates should have a Master's or Ph.D. degree in Computer Science, Operations Research, Statistics, Applied Mathematics, or a related engineering discipline, along with a minimum of 3 years of hands-on experience applying operations research and machine learning techniques.
Which programming languages and tools are essential for this role?
A strong proficiency in Python programming, machine learning libraries, and SQL is essential for the Data Scientist position.
What experience with cloud technologies is preferred?
Experience working with cloud technologies, preferably Google Cloud Platform (GCP), is preferred for the Data Scientist role.
What are the key responsibilities for this Data Scientist position?
Key responsibilities include applying operations research methodologies and machine learning to solve complex business problems, developing data-driven solutions for forecasting and inventory planning, and effectively communicating findings to business stakeholders.
Is knowledge of supply chain concepts important for this role?
Yes, a comprehensive understanding of supply chain concepts, including forecasting, inventory planning, optimization, and logistics, is important for this role.
How important are communication skills in this position?
Excellent communication skills are crucial, as the candidate must effectively explain complex concepts in simple, easy-to-understand terms to business stakeholders at all levels.
What types of applications will the work focus on?
The work will focus on applications in areas such as Connected Vehicle, Smart Mobility, Advanced Operations, Manufacturing, Supply Chain, Logistics, and Warranty Analytics.
What methodologies should candidates be familiar with?
Candidates should be familiar with operations research methodologies such as linear programming, nonlinear programming, heuristics, and simulation, alongside machine learning techniques.
Is prior experience in the Automotive industry required for this position?
While prior experience in the Automotive industry is not explicitly stated, familiarity with industry-related supply chain and logistics concepts may be beneficial.