Amazon Web Services (AWS), Cloud Computing, Communication Skills, Data Management, Data Science, Demand Forecasting/Planning, Diversity, ERP (Enterprise Resource Planning), Engineering, Information Technology & Information Systems, Internet of Things, Lean Manufacturing, Manufacturing, Microsoft Windows Azure, Operations Planning, Predictive Modeling, Product Development, Product Engineering, Production Planning, Production Systems, Prototyping, Python Programming/Scripting Language, Root Cause Analysis, SQL (Structured Query Language), Scalable System Development, Six Sigma, Supervisory Control and Data Acquisition (SCADA), Testing
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!
Role: Data Scientist
Location: Remote, USA
Duration: Fulltime Employee
Job Overview:
- 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.
Must Have:
- 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.
- Data Science Proven track record building and deploying ML models for predictive maintenance, anomaly detection, demand forecasting, and root cause analysis.
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.