Data Scientist Controls Engineer (LAP)

We are seeking a highly analytical and results-oriented Data Scientist with 3 years of experience specializing in leveraging IIoT data from manufacturing environments (Rockwell PLCs/VFDs, ControlLogix) to drive operational improvements and develop intelligent solutions. Proficient in the end-to-end data science lifecycle, from data ingestion (MQTT) and cloud-based processing (GCP) to advanced ML modeling (Python, SQL) and the development of interactive UIs and dashboards. Passionate about translating complex industrial data into actionable insights for smart factory initiatives. 

What you’ll do…

• 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.

You'll have... 

• 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.