
Data Scientist Controls Engineer (LAP)
- Louisville, KY
- Permanent
- Full-time
- 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
- Dimensional Control Data Analysis
- Manufacturing & IIoT:
- Industrial Internet of Things (IIoT) Architectures & Principles
- Rockwell Automation Ecosystem: ControlLogix, PLCs, VFDs, Studio 5000 (conceptual understanding)
- Familiarity with Rockwell software (e.g., FactoryTalk suite, potentially Rockwell OPTICS if it's a data access/visualization tool)
- Manufacturing Processes & Equipment Data
- Machine Learning & Statistical Analysis:
- Predictive Maintenance, Anomaly Detection, 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:
- 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 to both technical and non-technical stakeholders.
- Create comprehensive reports, projections, and visual presentations.
- Adhere to established guidelines and contribute to strategic discussions.
- Bachelor's Degree in a quantitative field (e.g., Data Science, Mathematics, Statistics, or related discipline).
- 3+ years of experience in advanced data analytics and model development.
- 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.
- 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.