Role Overview

Data Scientist (Contract-W2)

Responsibilities

Work hands-on with shop floor operations, production planning, and industrial systems including MES, SCADA, and ERP.
Bridge OT/IT systems to enable real-time data extraction.
Apply analytics and operational metrics such as:
- OEE
- Six Sigma, SPC
- Lean methodologies to improve yield, uptime, and efficiency.
Build scalable data pipelines for high-volume manufacturing/IoT data.
Develop and deploy machine learning models for:
- Predictive maintenance
- Anomaly detection
- Demand forecasting
- Root cause analysis
Communicate insights effectively to operations and executive stakeholders.
Validate and quantify process changes via:
- A/B experiments and simulations

8–10 years of Data Science experience.
Strong SQL and Python.
Industrial protocols experience: OPC-UA, MQTT, Modbus.
Industrial data engineering with lakehouse/medallion patterns using platforms such as Databricks, Snowflake, AWS, or Azure.
ML experience with scikit-learn, TensorFlow, or PyTorch and moving models from prototype to production.
Solid statistical foundations (e.g., time series, regression, clustering, hypothesis testing).

2–3 years in manufacturing (preferred).
Strong grounding in manufacturing quality improvement methods (Six Sigma/Lean/SPC).