Key Responsibilities:

1. Apply statistical, machine learning, and data science methods to solve complex business and scientific problems.
2. Lead development and deployment of predictive models and multivariate analytics for process monitoring, anomaly detection, and performance optimization
3. Collaborate with cross-functional teams (manufacturing, quality, IT) to identify, design and implement data-driven solutions which can drive measurable value. Partner with technical teams to resolve data gaps, inconsistencies, and support validation activities
4. Translate business problems into analytics approaches, define success metrics, and communicate recommendations to technical and non-technical audiences. Drive exploratory analysis, trend analysis, forecasting, and modeling using multiple sources of data.
5. Contribute to the development and deployment of AI-enabled solutions, including machine learning and generative AI use cases where appropriate. Facilitate knowledge transfer, training, and adoption of solutions across global teams
6. Work with Information Technology teams at organisation to deliver secure, scalable analytics products (dashboards, data products, model services) and manage project interdependencies
7. Integrate and transform data from Azure Data Lake (ADLS), Databricks, Enterprise applications, and other data sources to create scalable reporting and analytics solutions. Leverage data visualization and reporting tools (Power BI, SEEQ) for actionable insights.
8. Support integration and harmonization of data across Historian, MES, LIMS, ERP, and analytics platforms
9. Ensure data quality,



integrity, and compliance with GMP and regulatory standards. Maintain documentation, best practices, and knowledge repositories for analytics solutions
10. Track and report analytics project progress, risks, and outcomes to leadership and stakeholders. Monitor adoption KPIs, gather user feedback, and drive continuous improvement in analytics capabilities

Educational Qualifications:

- Bachelor’s degree in Data Analytics, Computer Science, Information Systems, Engineering, Statistics, Business Analytics, or related fields.
- 5–8 years of experience in data science, analytics, or digital deployment within the pharmaceutical or batch process manufacturing industry

Certifications Preferred:

- Certification/Training completion in SEEQ and OsiPi (AVEVA)
- Certifications in Microsoft Fabric, Power BI, Power Platform
- Certifications related to Databricks

Technical skills required

- Expert level on Time series data analytics – SEEQ, AVEVA (OSiPi) Vision
- Expert level on Business Intelligence – M
- MS Fabric (PowerBI, Power Automate, Power app)
- Familiarity with using Enterprise applications – Data Historian, MES, LIMS, SAP, QMS
- Familiarity with Project Management tools – JIRA or any other





Experience Required:

1. Domain Experience

· Strong understanding of pharma manufacturing unit operations and process monitoring concepts. Experience of working as part of Continued process verification (CPV), Annual Product Quality review (APR-PQR) documentation would be advantageous.

· Required domain knowledge of GxP regulations, audits, data integrity concepts.

· Understanding of Software Development Lifecycle (SDLC) stages, various environments, testing scripts, documentation, validation

1. Descriptive Analytics

· Hands-on experience developing dashboards and reporting solutions using Power BI by connecting to data sources and creating measures, table relationships

· Experience on Data modelling into Star & Snowflake schema for DIM & FACT tables

· Working experience on Integrated Development setting like VS Code

· Strong proficiency in writing SQL queries and performing various joins

1. Diagnostic and Predictive Analytics

· Expertise in multivariate statistical models (e.g., PCA/PLS) & predictive models and for near real time process monitoring, anomaly detection, and performance optimization

· Experience in design and visualize the time series data on overlay plots by creating event frames

1. Data connectivity

· Familiarity with cloud analytics (Azure/AWS), data pipelines, and APIs; experience with NLP for unstructured manufacturing knowledge is preferred

· Familiarity with machine learning, AI, and gen AI concepts and practical applications.

📌 Manager - Manufacturing Analytics (Telangana)
🏢 Viatris
📍 Telangana