Jobs · Information Technology · Texas

Data Scientist

ektello · Austin, TX · Today
Information Technology$64–$67/hrContract

Key Responsibilities

  • Translate plant and business problems into measurable analytical questions and use cases.
  • Identify, access, and assess data from MES, quality systems, equipment historians, maintenance systems, production systems, and other manufacturing sources.
  • Build reliable analytical datasets and pipelines using SQL, Python, Spark, and Databricks.
  • Perform exploratory analysis, statistical studies, root-cause analysis, forecasting, optimization, and experimentation.
  • Develop, validate, document, and monitor predictive or prescriptive models for use cases such as downtime, scrap, defects, bottlenecks, anomaly detection, yield, and preventive maintenance.
  • Evaluate data quality, lineage, coverage, missingness, bias, and operational readiness before modeling.
  • Create dashboards, visualizations, reports, and user interfaces that clearly communicate trends, risks, and opportunities.
  • Productionize analytics and models in partnership with data engineering, application, and Manufacturing IT teams.
  • Monitor model performance, data drift, pipeline health, and business impact after deployment.
  • Support manufacturing modernization initiatives, including cloud migration, data-product development, automation, and legacy-system retirement.
  • Follow data, cybersecurity, AI governance, safety, privacy, and change-management requirements.
  • Present technical results to both technical and nontechnical audiences and maintain clear documentation.
  • Promote reusable analytical methods, standards, and best practices across plants and manufacturing domains.

Qualifications

  • Education - Bachelor's degree in a technical field such as computer science, computer engineering or related field required.
  • Years of experience – at least 8-10 years of experience.
  • Experience technologies including SQL, Python, Spark, and Databricks.
  • Data modeling at least 8-10 years of experience.
  • Data pipeline at least 8-10 years of experience.
  • Data analytics – able to build something out of messy data at least 8-10 years of experience.

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