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 AI, Machine Learning, Cloud, Advanced Analytics. 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, Customer Experience, 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 team 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. This role will be an individual contributor role. which requires a strong foundation in data science methodologies, technical skills, and the ability to collaborate effectively with various stakeholders to translate business needs into solvable data science problems. You will play a crucial role in quantifiable contributions to business goals through models, experiments, and insights, while maintaining high standards of quality.
Responsibilities
Build an in-depth understanding of the problem domain and available data sources
Extract and Analyze data from GCP tables, data warehouse/data marts to discover insights, trends and patterns relevant to the business problem
- Support existing analytical products, LLM model and associated pipelines. Propose improvements to existing models or analyses when needed.
AI first approach, artificial intelligence at the core of a business's operations, products, and strategy
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. Collaborate across teams as needed and share findings effectively to varied audiences.
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.
- Produce clear documentation for data sources, transformations, assumptions, analyses, models, and experiments.
Work with business partners through problem formulation, data management, solutions development and operationalization
Technical Skills:
Strong Proficiency in Python, Statistics, SQL, Visualization
AI, LLM framework, Machine Learning frameworks
Working knowledge in GCP cloud environment
Nice to have: API Development, Familiarity with Agile development cycle
Functional Skills:
Problem Formulation & Problem-Solving Skills
Business Acumen
Ownership mindset, Proactive learner, Strong bias for action
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
BE, B.Tech, M.S./Masters in data science, Statistics, Computer Science, Applied Mathematics or a related engineering discipline
Minimum 3 years of hands-on experience in building end to end AI/ML based solutions for solving business problems
Strong proficiency in Python, data science libraries ((e.g., Scikit-learn, XGBoost, TensorFlow/PyTorch basics), SQL
Demonstrated technical skills in Data Wrangling, Data Visualization, Statistical Analysis, Programming, Machine Learning
- Strong understanding of core data science concepts, including statistics, probability, and machine learning basics.
Experience working with Google Cloud Platform (GCP) for building data pipelines, AI models, and model deployment (BigQuery, VertexAI, Dataform, API)
