Data Scientist (LAP)

Ford Motor • Louisville, KY

7d • Onsite

About The Position

As part of Ford Motor Company’s Manufacturing team, the Data Scientist will use manufacturing IIoT data to drive operational improvements and develop intelligent solutions for smart factory initiatives. The role covers the data science lifecycle, including data ingestion using MQTT, cloud-based processing on GCP, machine learning and statistical modeling, and building interactive user interfaces and dashboards. The position involves analyzing complex industrial data and turning it into actionable insights for manufacturing operations.

The Data Scientist develops and validates models, gathers and analyzes structured and unstructured data, researches analytical methods, and collaborates with cross-functional teams to define objectives and deliver insights. The role also includes interpreting and presenting results, preparing reports and projections, and contributing to strategic discussions while following established guidelines.

Requirements

• Bachelor’s degree in a quantitative field or 5+ years of experience in Data Science, IT, Statistics, or a related discipline.
• Proficiency in Python, R, SQL, or similar programming languages and tools.
• Strong skills handling structured and unstructured datasets for reporting and modeling.
• Excellent communication skills, including the ability to simplify complex concepts for diverse audiences.
• Ability to work independently and exercise sound judgment on technical approaches.

Nice To Haves

• Expertise in machine learning techniques, including predictive modeling, clustering, and regression analysis.
• Experience with Python libraries and frameworks such as Pandas, NumPy, Scikit-learn, TensorFlow or PyTorch, Dash or Streamlit, and Flask or FastAPI.
• Experience with SQL advanced querying, stored procedures, and query optimization.
• Experience with GCP services including BigQuery, Google Cloud Storage, Vertex AI, Dataflow, Pub/Sub, and Dataproc.
• Knowledge of MQTT, ETL/ELT data pipelines, data cleaning and preprocessing, data integration, and data mining.
• Knowledge of IIoT architectures and principles and the Rockwell Automation ecosystem, including ControlLogix, PLCs, VFDs, and Studio 5000.
• Familiarity with manufacturing data access and visualization tools and manufacturing equipment data.
• Experience with quality control or prediction, process optimization, time-series analysis, classification, regression, clustering methods such as OPTICS and DBSCAN, statistical modeling, and hypothesis testing.
• Experience with dashboarding tools such as Tableau, Power BI, Looker, Dash, Streamlit, or Bokeh; UI/UX principles for data applications; and data storytelling.
• Knowledge of Git, Agile methodologies, and basic API development.

Responsibilities

• Develop and validate machine learning and statistical models to support business strategy.
• Gather, manage, and analyze structured and unstructured data for reporting and analytics.
• Research and apply innovative analytical methodologies and techniques.
• Collaborate with cross-functional teams to define objectives and develop actionable insights.
• Interpret and present analytical results.
• Create comprehensive reports, projections, and visual presentations.
• Adhere to established guidelines and contribute to strategic discussions.
• Apply IIoT data and analytical methods to drive manufacturing operational improvements and smart factory initiatives.

Benefits

• Immediate medical, dental, and prescription drug coverage.
• Flexible family care, parental leave, new parent ramp-up programs, and subsidized back-up childcare.
• Family-building benefits, including adoption and surrogacy expense reimbursement and fertility treatments.
• Vehicle discount program for employees and family members, and management leases.
• Tuition assistance.
• Employee resource groups.
• Paid time off for individual and team community service.
• Paid holidays, including the week between Christmas and New Year’s Day.
• Paid time off and the option to purchase additional vacation time.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level