[Remote] Staff Engineer - Data Scientist

Note: The job is a remote job and is open to candidates in USA. Nagarro is a Digital Product Engineering company that builds products, services, and experiences across all devices and digital mediums. They are seeking a Data Scientist who will be responsible for manufacturing data analysis, building scalable cloud data pipelines, and translating complex model outputs into actionable recommendations for stakeholders.

Responsibilities

• Manufacturing 8–10 years in manufacturing (optional) with 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
• 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

Skills

• Minimum 6 years of experience as Data Scientist
• Strong SQL and Python proficiency with hands-on experience in medallion/lakehouse architectures on Databricks, Snowflake, AWS, or Azure
• 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
• Skilled in building scalable cloud data pipelines for high-volume manufacturing and IoT data using Spark, Kafka, Airflow, and Delta Lake
• 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
• Proven track record building and deploying ML models for predictive maintenance, anomaly detection, demand forecasting, and root cause analysis
• Manufacturing 8–10 years in manufacturing with hands-on experience in shop floor operations, production planning, and systems including MES, SCADA, and ERP

Company Overview

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