Data Analytics Manager

Key Skills required

The role involves applying advanced analytics, machine learning, and statistical modeling to optimize plant operations, enhance process efficiency, improve product quality, ensure sustainability, and reduce costs. Knowledge in OSI-PI Software and Data Analytics Platform, such as Seeq, Aspen Tech, and Python, is preferred.

Role & responsibilities

1. Collect, clean, and analyze large-scale structured and unstructured data from plant operations (sensors, DCS/SCADA systems, ERP, MES, laboratory data).
2. Develop predictive and prescriptive models for: Process optimization (yield, throughput, energy efficiency). Equipment reliability and predictive maintenance. Quality control and anomaly detection. Supply chain and inventory management.
3. Partner with process engineers, R&D, and operations teams to identify opportunities for data-driven improvements.
4. Deploy machine learning models in real-time production environments.
5. Build dashboards and visualization tools for plant monitoring and decision support.
6. Ensure data governance, model validation, and compliance with safety and regulatory standards.
7. Drive initiatives in digital twin modeling, Industry 4.0, and smart manufacturing.
8. Probability theory (Mathematical foundations), Statistical Inference (Hypothesis testing, Probability Distributions, parametric and non-parametric methods), Machine learning (Classification, Regression, Clustering, model evaluation, Ensemble methods)
9. Knowledge of Programming, such as Python, MATLAB, and Hysis tools preferred.
10. Knowledge in OSI Soft, Process Data analytics Platform such as Seeq, Trend Miner, and Aspen Tech preferred.

Preferred candidate profile

Data Scientist with expertise in chemical manufacturing and process industries to drive data-driven decision-making across our chemical plants with 3-5 years of Experience in Data analytics.