Senior Staff Engineer - Data Scientist

Nagarro is a Digital Product Engineering company that builds products, services, and experiences across all devices and digital mediums. They are seeking a Senior Staff Engineer - Data Scientist with extensive experience in data science and a strong background in manufacturing to drive measurable gains in yield, uptime, and efficiency through advanced data engineering and analytics.

Responsibilities:

• 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

Requirements:

• 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
• 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