Research Engineer - Virtual Vehicle Prototypes - Data Analytics

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

At Ford Motor Company, we believe freedom of movement drives human progress. We also believe in providing you with the freedom to define and realize your dreams. With our incredible plans for the future of mobility, we have a wide variety of opportunities for you to accelerate your career potential as you help us define tomorrow’s transportation.

Ford’s Research and Advanced Engineering team explores new vehicle and societal innovations that require some level of invention before they can be applied to our products and services. The team is building on a history of Ford innovation, including our invention of the three-way catalytic converter to modernize vehicle emissions controls in the 1970s and the world’s first rear inflatable seat belts in 2010.

Today, we are exploring and delivering ways to make smarter vehicles and our transportation system more efficient to improve people’s lives by helping them move more freely, safely and enjoyably. For example, we are changing how our products are made by creating high-quality vehicles in an environmentally and socially responsible way, including the use sustainable materials. Since 2000, we have used 12 industry and world-first plant-based materials in our production vehicles. We also are researching the possible use of tomato skin, bamboo, agave fiber, dandelion roots, algae and coffee chaff as part of our ambitious goal of making our vehicles with up of 20 percent sustainable material by 2025.

What you will be able to do

Engineering complex electrified propulsion systems in today’s competitive market requires sophisticated model-based development methodologies that can help deliver optimized products quickly and efficiently. There is a critical need to efficiently explore and identify high leverage system opportunities for improving the customer user experience and value of our electrified vehicle products. The candidate for this position would address this need by serving as a data scientist to generate and analyze large-scale testbed, connected vehicle and simulation data sets for insights that aid in improving engineering efficiency and customer experience. You will:

• Analyze large-scale testbed/simulation data and generate mathematical models (e.g. statistical, machine learning, etc.) to capture system behaviors
• Develop and automate processes to visualize large-scale customer data using intuitive dashboards to characterize on road vehicle propulsion performance
• Analyze connected vehicle data to extract customer usage information that can be used for virtual vehicle prototype validation and design of next generation of Ford xEVs
• Develop and apply novel methods, including use of simulation, for generating large sets of on road trip data
• Work as a liaison to Ford Global Data Insights and Analytics and acquire relevant data to meet Propulsion Systems Analysis department needs
• Function as the primary data scientist for Propulsion Systems Analysis department

The minimum requirements we seek

• Master’s Degree in Computer Science or Engineering
• 2+ years of combined experience with following:
  • Using Python or other programming languages for data analysis
  • Developing analytical/machine learning models using common libraries (e.g. SciPy, TensorFlow, Keras, etc.)
  • Retrieving, cleaning and visualizing Big Data using tools (e.g. Hadoop, Spark, Hive, Alteryx, Tableau, etc.)
  • Developing productionized analytical models and interactive visualizations

Our preferred requirements

• Experience with electrified propulsion system operations and key interactions of vehicle systems, components and controls
• Experience with physical system modeling and simulation
• Experience using source control and continuous integration tools to manage data analysis work products and processes (e.g. Git, Jenkins, Travis CI, etc.)
• Excellent organizational skills including attention to detail and multi-tasking skill