Quick Overview
Work Type
Hybrid
Level
Mid Senior
Job Description
- 5+ years of experience required as Data Scientist
- 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.
Job Overview:
- Data Engineering Skilled in building scalable cloud data pipelines for high-volume manufacturing and IoT data using Spark, Kafka, Airflow, and Delta Lake.
- Strong communicator able to translate complex model outputs into clear, actionable recommendations for operations and executive stakeholders.
- Experience designing A/B experiments and simulations to validate process changes and quantify business impact before full deployment.
Good to have skills:
- 2-4 years working in manufacturing domain.
- 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.
- Proficient in scikit-learn, TensorFlow, or PyTorch with experience moving models from prototype to production in industrial environments.
- Solid grounding in statistical methods time series, regression, clustering, and hypothesis testing applied to manufacturing quality problems.
Skills
SQL
AWS
Scikit-learn
Snowflake
Airflow
Azure
ERP
Databricks
Forecasting
SCADA
IoT
Kafka
PyTorch
Python
Root Cause Analysis
Six Sigma
TensorFlow
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