Data Scientist
PeopleNTech
Title / Designation - Data Scientist
Experience Required Overall: 8-10 years
Duration - 6 months + Extension possible
Work Model - Remote (USA), with 25%-30% travel required across USA
Visa - Independent
Number of Internal interviews with Nagarro - 1 (Technical)
Client Interviews - 2 (1 Technical & 1 Functional Cultural fit)
Mode of Interviews - Virtual
Tentative start date - ASAP
Rate - USD $95/ hour on C2C all inclusive.
Job Description :
Experience Required Overall: 8-10 years
Duration - 6 months + Extension possible
Work Model - Remote (USA), with 25%-30% travel required across USA
Visa - Independent
Number of Internal interviews with Nagarro - 1 (Technical)
Client Interviews - 2 (1 Technical & 1 Functional Cultural fit)
Mode of Interviews - Virtual
Tentative start date - ASAP
Rate - USD $95/ hour on C2C all inclusive.
Job Description :
- 8-10 years of experience as a Data Scientist, with 2-3 years in manufacturing (preferred)
- Hands-on 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.
Vacancy posted 3 days ago
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