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Senior Staff Engineer - Data Scientist

Roles & Responsibilities

  • 8-10 years of overall data science experience
  • 2-4 years of manufacturing/domain experience (hands-on shop floor operations, MES/SCADA/ERP)
  • Proven track record deploying ML models for predictive maintenance, anomaly detection, and demand forecasting in industrial environments
  • Strong data engineering and cloud analytics skills: scalable data pipelines with Spark, Kafka, Airflow, and Delta Lake; SQL and Python proficiency; experience with Databricks/Snowflake/AWS or Azure

Requirements:

  • Translate complex model outputs into clear, actionable recommendations for operations and executive stakeholders
  • Lead end-to-end ML lifecycle for industrial use cases (predictive maintenance, anomaly detection, demand forecasting) from prototype to production, with validation experiments
  • Build and maintain scalable cloud data pipelines for high-volume manufacturing and IoT data using Spark, Kafka, Airflow, and Delta Lake; manage lakehouse architectures on Databricks, Snowflake, AWS, or Azure
  • Bridge OT/IT by integrating industrial protocols (OPC-UA, MQTT, Modbus) to enable real-time data extraction and improve OEE, uptime, and efficiency

Job description

Company Description

We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work on a scale across all devices and digital mediums, and our people exist everywhere in the world (17000 plus experts across 39 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in!

Job Description

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.

Additional Information

Disclaimer: Nagarro is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will be afforded equal employment opportunities without discrimination based on race, creed, color, national origin, sex, age, disability, or marital status.

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