Role – Data Science Engineer / Data scientist
Experience Required Overall: 8-10 years
Domain Experience – Manufacturing 2-4 Years
Duration- 6 Months Contract to hire
Work Model – Remote with travel across USA
Job Overview:
- 8–10 years of overall data science experience required along with 2-4 years working in manufacturing domain.
- Hands-on experience in shop floor operations, production planning, and systems including MES, SCADA, and ERP.
- Proficient in industrial protocols (OPC-UA, MQTT, Modbus) with ability to bridge OT/IT systems for real-time data extraction.
- Applied experience with OEE, Six Sigma, SPC, and lean methodologies to drive measurable gains in yield, uptime, and efficiency.
- Data Engineering Skilled in building scalable cloud data pipelines for high-volume manufacturing and IoT data using Spark, Kafka, Airflow, and Delta Lake.
- Strong SQL and Python proficiency with hands-on experience in medallion/lakehouse architectures on Databricks, Snowflake, AWS, or Azure.
- Data Science Proven track record building and deploying ML models for predictive maintenance, anomaly detection, demand forecasting, and root cause analysis.
- Proficient in scikit-learn, TensorFlow, or PyTorch with experience moving models from prototype to production in industrial environments.
- Strong communicator — able to translate complex model outputs into clear, actionable recommendations for operations and executive stakeholders.
- Solid grounding in statistical methods — time series, regression, clustering, and hypothesis testing applied to manufacturing quality problems.
- Experience designing A/B experiments and simulations to validate process changes and quantify business impact before full deployment.