Staff Engineer – Data Scientist

🔥 1 minute ago

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Nagarro

10,000+ employees

Founded 1996

🤝 B2B

🏢 Enterprise

B2B • Enterprise • Technology Consulting

Nagarro is a global leader in digital engineering and technology consulting. The company helps clients become innovative, digital-first businesses by leveraging technology to drive business breakthroughs. Known for its entrepreneurial agility and CARING mindset, Nagarro offers a wide range of services, including digital engineering, intelligent enterprise solutions, and experience and design services. With over 17,900 employees across 37 countries, Nagarro collaborates with industry leaders to accelerate digitalization and technology-led innovation.

📋 Description

• 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. • 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.

🎯 Requirements

• 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. • Proven track record building and deploying ML models for predictive maintenance, anomaly detection, demand forecasting, and root cause analysis.

🏖️ Benefits

• Employees can work remotely

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