We are looking for a Data Scientist to work on material cost analytics problems. The successful candidate will be a fearless data explorer who enjoys data wrangling, a resourceful problem solver who is energized by difficult business problems, a savvy statistician who understands advanced modeling frameworks and their limitations, a proven communicator who effectively interfaces between technical and business teams, and a reliable team player. – Smart. Nice. Curious. Committed.

Our Data Scientists help bring data to life to solve business problems.  They work collaboratively to design analytical solutions that harness internal and external data, and leverage visualizations, predictive analytics, and prescriptive methods, to help the right decision makers make the right decisions at the right time. As a Data Scientist on the team, you will collaborate with partners in Product Development, Supply Chain and other Ford functions to define problems, identify data, develop data pipelines, develop machine learning algorithms, leverage operations research techniques, and deploy software solutions to provide actionable insights that deliver measurable, transformational benefits to Ford. 

Responsibilities: 

• Acquire deep understanding of the business problems and translate them into appropriate mathematical representations
• Work with large, complex data sets using tools such as SQL, Python, DBT
• Find opportunities for applying advanced statistical and machine learning techniques, Large Language Models and Generative AI to develop solutions for real world, non-routine, large scale Design Cost analytics problems
• Develop and deliver business solutions using skills such as data acquisition, data engineering, programming, and visualization. 
• Develop and deliver analytic products using skills such as statistical analysis, machine learning, algorithm design, and interface development
• Interpret modeling results and communicate them to technical and non-technical audiences, cross-functional teams and leadership
• Interact and work cross-functionally with a wide variety of teams to implement the ideas into solutions
• Develop trust with stakeholders and peers by delivering results on time
• Ensure overall quality of the data & solutions throughout the analytic development process
• Work with business teams on change management
• Provide training and maintenance of implemented tools to business partners
• Collect feedback from business users and continuously improve the analytic products

Basic Qualifications:

• Bachelor’s degree in Statistics, Data Science, Computer Science or a related quantitative discipline
• 2+ years of experience in at least one statistical software package such as Python, using SQL / DBT for acquiring and transforming data
• Experience with Google Cloud Platform
• 2+ years experience in a data science / artificial intelligence-related role

Preferred Qualifications:

• MS or PhD in quantitative field, such as Statistics, Computer Science, Economics, Mathematics, Data Science, Operations Research
• 4+ years of post-graduate work experience with Python, SQL, DBT 
• 4+ years of post-graduate work experience in data mining, statistical analysis, modeling, optimization 
• 2+ years of experience with Google Cloud Platform and GCP-native tools
• 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
• Ability to effectively advocate technical solutions to peer, management and business audiences 
• Well-organized, a self-starter, independent and ready to work with minimal supervision
• A respectful and committed teammate, willing to excel and work with talented people
• Proven quantitative modeling and statistical analysis skills
• Excellent programming skills, particularly in interface development using Python is very desirable
• Work experience in automotive industry is a big plus, as is experience with design optimization and design cost reduction.