Data Scientist

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.

Creating the future of Ford requires the highly intelligent use of data, metrics, and analytics. That’s where you can make an impact as part of our Global Data Insight & Analytics team. We are the trusted advisers that enable Ford to clearly see business conditions, customer needs, and the competitive landscape. With our support, key decision-makers can act in meaningful, positive ways. Join us and use your data expertise and analytical skills to drive evidence-based, timely decision-making.

The Global Data Insights and Analytics (GDI&A) department is looking for qualified people who can develop scalable solutions to complex real-world problems using Machine Learning, Big Data, Statistics and Optimization. The goal of GDI&A is to drive evidence-based decision making by providing insights from data. Applications for GDI&A include, but are not limited to, Connected Vehicle, CX Analytics, Advanced Operations, Manufacturing, Supply chain, Logistics, and Warranty Analytics.

Ford Customer Service Division, within Ford, is committed to provide our customers the “Always On” experience and our mission is to get our customers back on the road, in the shortest possible time. FCSD is a true one-stop shop, offering comprehensive Diagnostics, Repair & Service Capabilities for a full portfolio of Electrified, Hybrid and Internal combustion vehicles globally.

Build analytical solutions that support

• Dealers to Diagnose, Repair & Service our vehicles
• Customers for a seamless Service experience
• A highly Profitable, Critical and Complex Parts & Service business
  
  
  

A Data Scientist who can enable FCSD-Service Engineering operations business by building and delivering impactful analytical products adhering to the best practices in AI/ML space exhibiting Ford OS behaviours will certainly be a great fit for this role.

Responsibilities

Job Responsibilities

• Build an in-depth understanding of the problem domain and available data sources
• Extract and Analyse data from GCP tables, data warehouse/data marts to discover trends and patterns
• Support existing analytical products, LLM model and associated pipelines.
• Closely collaborate with business partners, data engineers and product owner
• Build analytical solutions to drive business value ensuring data-driven decisions
• Communicate insights and results to business teams, senior leadership through presentations.
• Design and implement scalable analytical solutions (Dashboards, statistical models, AI/ML models) in cloud environment.
• Train, test and operationalize models for business use cases; integrates models with upstream and downstream business processes.
• Work with business partners through problem formulation, data management, solutions development and operationalization
  
  
  

Technical Skills:

• Python, Statistics, SQL, Visualization, GCP (Preferred), Machine Learning frameworks, Gen AI/LLM development
• Nice to have: API Development, Familiarity with Agile development cycle
  
  
  

Functional Skills:

• Problem Formulation & Problem-Solving Skills
• Ownership mindset
• Clear and coherent communication, both verbal and written
• Proactive learner, Strong bias for action
  
  
  

Qualifications

• Bachelor’s/master’s degree in data science, Statistics, Computer Science, Applied Mathematics or a related engineering discipline
• Strong proficiency in Python (ML Packages), SQL
• Demonstrated technical skills in Data Wrangling, Data Visualization, Statistical Analysis, Programming, Machine Learning
• Minimum 3 years of hands-on experience in building AI/ML models for solving business problems
• Experience working with cloud technologies, preferably Google Cloud Platform (GCP) for building data pipelines, model deployment
• Well-organized, independent, and ready to work with minimal supervision
• Comfortable working in an environment where problems are not always well-defined
• Strong interpersonal skills with ability to communicate complex topics to business, leaders, peers in a simple and clear manner