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)