Job Title: Data Scientist
Client: American Automotive Company
Duration: 4 months contract with HIGH chance to become permanent
Location: Austin, TX (Onsite)
Work Authorization: Visa sponsorship not available (Not open to C2C or 1099)
Pay: $64-67/hr w2 + Benefits/PTO
Top Required Skills
- 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
Position Overview
The Data Scientist applies statistics, machine learning, optimization, and programming to manufacturing data to improve safety, quality, throughput, cost, equipment reliability, and decision-making across plants. The role partners closely with Manufacturing IT, plant operations, engineering, quality, maintenance, and data engineering teams.
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.
- Convert findings into practical recommendations that plant personnel and leaders can use in daily decisions.
- 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