Data Scientist - Manufacturing Analytics

<h2>Must-Have Skills / Requirements</h2><ul>
<li>
<strong>6+ years of experience</strong>in Data Science / Advanced Analytics</li>
<li>Hands-on experience in manufacturing / industrial / plant environments</li>
<li>Strong working knowledge of Seeq (industrial analytics platform) for time-series analysis, including both Seeq Workbench and Data Lab (using the seeq spy library).</li>
<li>Proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL</li>
<li>Strong understanding of:</li>
<ul>
<li>Machine Learning (regression, anomaly detection, predictive models)</li>
<li>Statistical modeling and hypothesis-driven analysis</li>
<li>Time-series / sensor data analytics</li>
</ul>
<li>Experience building and deploying predictive models for:</li>
<ul>
<li>Predictive maintenance</li>
<li>Process optimization</li>
<li>Quality and yield improvement</li>
</ul>
<li>Ability to work with sensor data, process data, and operational datasets</li>
<li>Strong analytical thinking, troubleshooting, and root-cause analysis capability</li>
</ul><h2>Good-to-Have Skills</h2><ul>
<li>Experience in industries such as:</li>
<ul><li>Oil &amp; Gas, Chemicals, Manufacturing</li></ul>
<li>Knowledge of MLOps (model deployment, monitoring, pipelines)</li>
<li>Exposure to optimization techniques for industrial processes</li>
<li>Exposure to cloud platforms (Azure / AWS / GCP)</li>
<li>Familiarity with data visualization tools, real-time / streaming data analytics, data engineering (ETL / data pipelines / data lakes)</li>
</ul><h2>Roles &amp; Responsibilities</h2><ul>
<li>Analyze manufacturing plant and process data to identify patterns, anomalies, and optimization opportunities</li>
<li>Use Seeq platform for:</li>
<ul>
<li>Time-series analysis</li>
<li>Root cause investigation</li>
<li>Process monitoring and visualization</li>
</ul>
<li>Develop and deploy machine learning models for:</li>
<ul>
<li>Predictive maintenance</li>
<li>Process efficiency improvement</li>
<li>Quality / yield optimization</li>
</ul>
<li>Work closely with plant, engineering, and operations teams to understand real-world process issues</li>
<li>Translate business and operational challenges into data science solutions</li>
<li>Build and maintain data pipelines, analytical datasets, and workflows</li>
<li>Monitor, evaluate, and continuously improve model performance in production</li>
<li>Present actionable insights through dashboards, reports, and stakeholder discussions</li>
<li>Ensure data quality, reliability, and governance across manufacturing data sources</li>
<li>Drive adoption of data-driven decision-making across plant operations</li>
</ul>