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.
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.
REQUIREMENTS
- Bachelors Degree in a technical field such as computer science, computer engineering or related field required
- 8-10 years applicable experience required
- 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
- Experience with database technologies
- Knowledge of the ETL process
- Knowledge of at least one scripting language
- Strong written and oral communication skills
- Strong troubleshooting and problem solving skills
- Demonstrated history of success
- Desire to be working with data and helping businesses make better data driven decisions
#LI-CH1
