Principal Data Scientist

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.

Enterprise Technology plays a critical part in shaping the future of mobility. If you’re looking for the chance to leverage advanced technology to redefine the transportation landscape, enhance the customer experience and improve people’s lives, this is the opportunity for you. Join us and challenge your IT expertise and analytical skills to help create vehicles that are as smart as you are.

You'll have...

Ph.D. in Computer Science, Statistics, Mathematics or a related field and 5 years of experience in the job offered or a related occupation.  5 years of experience with each of the following skills is required:  1. Data Science or advanced data engineering. 2. Python development (including Pandas, NumPy, and Scikit-learn) for data manipulation, analysis, and scripting.  3. Using Machine Learning frameworks and libraries including at least 5 of the following: Pyspark, BigQuery ML, Pandas, Scipy-Weave, Multiprocessing, Graph ML libraries, Neo4j, NLTK, or MatplotLib. 4. Designing, implementing, and deploying machine learning models for complex data problems including anomaly detection or predictive maintenance within data systems, including algorithm fine-tuning for performance and accuracy at scale.  5. Researching, evaluating, and integrating new ML capabilities, covering both foundational and cutting-edge approaches.  3 years of experience with the following skill is required:  1. Using SQL skills for querying, manipulating, and optimizing complex datasets, including query tuning.

We are offering a salary of $165,967.92 - $182,133.96/yr. 

You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!

As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder…or all the above? No matter what you choose, we offer a work life that works for you, including:

• Immediate medical, dental, and prescription drug coverage
• Flexible family care, parental leave, new parent ramp-up programs, subsidized back-up child care and more
• Vehicle discount program for employees and family members, and management leases
• Tuition assistance
• Established and active employee resource groups
• Paid time off for individual and team community service
• A generous schedule of paid holidays, including the week between Christmas and New Year's Day
• Paid time off and the option to purchase additional vacation time.

For a detailed look at our benefits, click here:

https://fordcareers.co/LL6

Candidates for positions with Ford Motor Company must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire.

We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status. In the United States, if you need a reasonable accommodation for the online application process due to a disability, please call 1-888-336-0660.

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What you'll be able to do:

Principal Data Scientist - positions offered by Ford Motor Company (Dearborn, Michigan). Note, this is a hybrid position whereby the employee will work both from home and from the aforementioned worksite. Hence, the employee must live within a reasonable commuting distance from the worksite. Design, build, and deploy end-to-end machine learning algorithms to tackle complex data challenges unique to platform. Developing identity resolution algorithms from scratch, refining for accuracy and performance at scale, and supporting production deployment. Lead efforts to identify, analyze, and resolve complex data quality issues across large-scale data warehouses and data lakes. Design and implement ML-driven monitoring tools for anomaly detection, data cleansing, standardization, and validation, ensuring high data integrity, reliability, and consistency from all sources. Contribute to developing internal tools, libraries, and automation scripts focused on enhancing data lineage, metadata management, and automated data quality checks. Building and managing Docker images and automating algorithms for efficient orchestration and scheduling. Apply advanced data science (statistical analysis, predictive modeling) to understand the performance, efficiency, and cost-effectiveness of large-scale data pipelines, ETL/ELT processes, and data storage solutions. Propose and implement data-driven improvements to optimize data flow, achieve sub-second latency, and enhance resource utilization. Use advanced analytical techniques for deep-dive root cause analysis on data discrepancies, performance bottlenecks, or system failures. Drive the strategic development of data science capabilities within the Product group, leading R&D efforts. Leverage Generative AI (LLMs) to identify problems and develop solutions within the data platform and data warehouse environment. Partner closely with data engineers and architects to design, optimize, and maintain scalable data structures and cloud-native data services. Manage the ingestion of data from various sources and formats into BigQuery and other data platforms. Implement robust transformation processes necessary for downstream analytical consumption. Act as a key liaison and project leader, mentoring data engineers and collaborating with global stakeholders. Translate complex business requirements into precise technical specifications for data solutions. Serve as a technical conduit between central privacy, product, and engineering teams for end-to-end system design. Create comprehensive documentation for data structures, data quality rules, and analytical findings related to the data platform. Share expertise, mentor junior team members, and foster best practices within the team and across the organization.