Apply on Employer Site

Ford Motor Company · 1 month ago

Data Scientist-Controls (LAP)

Louisville, KY

Full-time

Onsite

Mid, Senior Level

5+ years exp

Ford Motor Company is seeking a highly analytical and results-oriented Data Scientist to leverage IIoT data from manufacturing environments for operational improvements. The role involves managing the end-to-end data science lifecycle and developing intelligent solutions to translate complex industrial data into actionable insights.

AutomotiveAutonomous VehiclesManufacturingTransportation

No H1B

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

Qualification

PythonSQLGoogle Cloud PlatformMachine LearningData VisualizationData CleaningIndustrial Internet of ThingsAgile MethodologiesVersion ControlCommunication

Required

Bachelor's degree in a quantitative field or 5+ years of experience in Data Science, IT, Statistics, or a related discipline

Proficiency in tools and programming languages such as Python, R, SQL, or similar

Expertise in machine learning techniques, including predictive modeling, clustering, and regression analysis is desirable

Strong skills in handling structured and unstructured datasets for reporting and modeling

Excellent communication skills with the ability to simplify complex concepts for diverse audiences

Proven ability to work independently and exercise sound judgment on technical approaches

Programming & Databases: Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch, Dash/Streamlit, Flask/FastAPI), SQL (Advanced querying, stored procedures, query optimization)

Cloud Platforms & Big Data: Google Cloud Platform (GCP): BigQuery, Google Cloud Storage (GCS), Vertex AI, Dataflow, Pub/Sub, Dataproc

Data Technologies & Protocols: MQTT, Data Pipelines (ETL/ELT), Data Cleaning & Preprocessing, Data Integration, Data Mining

Manufacturing & IIoT: Industrial Internet of Things (IIoT) Architectures & Principles, Rockwell Automation Ecosystem: ControlLogix, PLCs, VFDs, Studio 5000 (conceptual understanding), Familiarity with software for data access/visualization tools, Manufacturing Environment & Equipment Data

Machine Learning & Statistical Analysis: Quality Control/Prediction, Process Optimization, Time-Series Analysis, Classification, Regression, Clustering (e.g., OPTICS, DBSCAN), Statistical Modeling, Hypothesis Testing

Visualization & UI/Dashboard Development: Dashboarding Tools (e.g., Tableau, Power BI, Looker, or Python libraries like Dash, Streamlit, Bokeh), UI/UX Design Principles for Data Applications, Data Storytelling

Software Development & Operations: Version Control (Git), Agile Methodologies, Basic API Development Responsibilities