Staff Engineer - Data Scientist at Nagarro
Grand Prairie, TX
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Jul 28, 2026
Grand Prairie, TX
Jul 29, 2026
What this job asks for AI summary
A full-time, primarily onsite Data Scientist role (4 days/week in Grand Prairie, TX) focused on manufacturing intelligence. The position involves building and deploying ML models for predictive maintenance, anomaly detection, demand forecasting, and root cause analysis, while also constructing scalable cloud data pipelines for high-volume manufacturing and IoT data. Candidates with a background bridging OT/IT systems and shop floor operations are strongly preferred.
Senior level · 6+ years · Dallas-Fort Worth-Arlington, TX · Full-time
“or” means any one of them counts — you don't need all of them.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 130 people in the Dallas-Fort Worth-Arlington, TX area plausibly meet what this posting asks for (data scientists). range 95–170
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $130,559 (middle half $92,500–$149,977).
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 29, 2026. It is a model, not a headcount.
Why we read it this way (5)
The posting lists 8–10 years of manufacturing experience as 'optional', so it is treated as preferred context rather than a hard gate.
The 'Must Have' section explicitly calls out SQL, Python, and lakehouse/medallion architectures on Databricks, Snowflake, AWS, or Azure — these are marked as required. Databricks and AWS are listed as the primary named tools with Snowflake and Azure as stated alternatives.
ML frameworks (scikit-learn, TensorFlow, PyTorch) and data pipeline tools (Spark, Kafka, Airflow, Delta Lake) appear in the narrative/job overview sections rather than the 'Must Have' block, so they are marked preferred.
Industrial systems (MES, SCADA, ERP) and protocols (OPC-UA, MQTT, Modbus) appear in the manufacturing context narrative and are marked preferred. OPC-UA is listed as the primary with MQTT and Modbus as alternatives since the posting treats them as a group of interchangeable industrial protocols.
The role is a strong Data Scientist (15-2051) fit given the ML/modeling focus; the alt code 15-1243 reflects the significant data pipeline/lakehouse engineering component.
Read the full posting
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