Data Scientist

Job Summary Analyze manufacturing plant and process data to deliver data-driven solutions that optimize operations. Develop and deploy machine learning models using Seeq and Python, collaborating with cross-functional teams to improve predictive maintenance, process efficiency, and quality outcomes. Responsibilities • Analyze manufacturing plant and process data to identify patterns, anomalies, and optimization opportunities • Perform time-series analysis, root cause investigation, and process monitoring using the Seeq platform (Workbench and Data Lab) • Develop and deploy machine learning models for predictive maintenance, process efficiency improvement, and quality/yield optimization • Collaborate with plant, engineering, and operations teams to translate business challenges into data science solutions • Build and maintain data pipelines, analytical datasets, and workflows to support operational analytics • Monitor, evaluate, and continuously improve model performance in production environments • Present actionable insights through dashboards, reports, and stakeholder discussions to drive informed decision-making • Ensure data quality, reliability, and governance across manufacturing data sources • Promote adoption of data-driven decision-making across plant operations Preferred competencies and qualifications • Experience in industries such as Oil & Gas, Chemicals, and Manufacturing • Knowledge of MLOps including model deployment, monitoring, and pipeline management • Exposure to optimization techniques for industrial processes • Familiarity with cloud platforms such as Azure, AWS, or GCP • Experience with data visualization tools, real-time/streaming data analytics, and data engineering (ETL, data pipelines, data lakes)