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Senior General Manager IT - AI, RPA, Data Science and Data Analytics
Senior General Manager IT - AI, RPA, Data Science and Data AnalyticsGlenmark Pharmaceuticals • Mumbai, Maharashtra, India
Senior General Manager IT - AI, RPA, Data Science and Data Analytics

Senior General Manager IT - AI, RPA, Data Science and Data Analytics

Glenmark Pharmaceuticals • Mumbai, Maharashtra, India
20 days ago
Job description

POSITION DETAILS :

Designation : Senior GM / Vice President IT - AI, RPA, Data Science & Data Analytics

Business Unit : Corporate

Function : IT

Location : Mumbai (HO)

Reporting to : Executive Vice President - Information Technology

ROLE OVERVIEW / PURPOSE :

To Architect, Implement, Enhance and Monitor AI / ML / RPA Automation IT Applications @ the Corporate level across functions / domains – R&D, Regulatory, Manufacturing, Quality, Sales, Procurement, Supply chain, Warehousing, HR, Legal, Finance, Corporate Communications, Data-warehousing and Analytics - Projects and Support in line with Organizational requirements and directives. To deliver end-to-end solution right from inception of idea till deployment and then Business as usual (BAU) support from Technology perspective.

The roles played : Some of the key roles that this position is expected to play :

Drive enterprise-wide digital transformation through Artificial Intelligence (AI), Robotic Process Automation (RPA), Data Science, and Data Analytics.

Lead initiatives aligned with strategic business goals, leveraging AI / ML, advanced analytics & intelligent automation to improve Product Lifecycle, Operations, R&D, Regulatory, Manufacturing, Quality, Sales, Supply chain, and Financial excellence

Key Interfacing Applications :

 SAP ECC and SAP S / 4 HANA

 LIMS – Labware

 Trackwise – QMS

 eCTD ( Extedo) – Electronic submissions

 OC / RDC – Oracle (CTMS)

 eBMR, Manufacturing Execution Systems (MES) - Werum

 L2 automation

 PLC Upgrades, CSV

 Track and Trace

 Artwork Management – Global Vision

 Robotic Process Automation / Artificial Intelligence

 Dashboards-Tableau, PowerBI

 Supply Chain, Scheduling, Supply Planning, Manufacturing Optimization

 Waters – Empower Systems in Quality Labs

 RA systems integration into Ops and Quality

 Microsoft Fabric as a Data Lake on top of M365 – Email, One Drive, Teams and SharePoint + Microsoft Co-Pilot go forward

 SAP – SAC - Analytics Cloud – SAP S / 4 HANA

OVERALL JOB RESPONSIBILITIES :

Responsibilities :

 Strategy & Roadmap

 AI / ML & Data Science Management

 Robotic Process Automation (RPA) Implementation

 Project Management & Governance

 Infrastructure, Cloud, and Integration Oversight

 Training awareness, User / Stakeholder Adoption & Documentation

A. Strategy & Roadmap

  • Define and execute the digital technology roadmap focusing on AI, RPA, and advanced analytics.
  • Collaborate with business leaders, and global teams to identify key automation and analytics use cases.
  • Evaluate emerging technologies for applicability in pharma operations (AI in Manufacturing, Quality, R&D, Regulatory, Supply Chain, Sales, Finance, Legal etc.)
  • Conduct daily team stand-ups with IT internal teams (Developer, Infra team)
  • Review Open task items for Project milestones / Support to ensure closure of same
  • Monitor deliverables across AI model development, RPA bot creation etc.
  • Review alignment of AI / RPA projects with business priorities and update executive sponsors.

B. AI / ML & Data Science Management

  • Identify and manage projects involving machine learning, predictive modelling, NLP, Generative AI, etc.
  • Collaborate with domain experts (R&D, Manufacturing, Quality, Regulatory, Sales, Supply Chain, Legal) to build and validate models.
  • Supervise Machine Learning Operations lifecycle : data collection, model training, evaluation, deployment, monitoring.
  • Develop AI applications / address use cases in R&D, Regulatory, Supply Chain, Manufacturing, Quality, Sales, Finance, Legal for process optimization, etc.
  • Review model training / testing status from data science team.
  • Oversee the pipeline for data ingestion, feature engineering, and versioning.
  • Evaluate preliminary results from AI / ML models – accuracy, bias metrics.
  • Provide direction on model fine-tuning, regulatory suitability.
  • Collaborate with domain experts (R&D, Regulatory, QA, Supply Chain, Finance, Legal etc.) for training data validation and accuracy.
  • C. Robotic Process Automation (RPA) Implementation

  • Identify and evaluate RPA opportunities in manufacturing, finance, HR, procurement, QA / QC
  • Oversee RPA implementation life cycle : process assessment, bot development, testing, deployment, monitoring.
  • Lead teams using tools like UiPath, Microsoft Power Automate
  • Implement intelligent automation (IA) by combining RPA with OCR, AI, NLP
  • Review RPA pipeline : Identify new automation candidates, prioritize based on Business priority / ROI.
  • Monitor daily performance of deployed bots (transaction logs, exception reports).
  • Approve process design documents (PDDs) and solution design documents (SDDs).
  • OVERALL JOB RESPONSIBILITIES

  • Address any production failures or exceptions in bot execution with development teams.
  • D. Project Management & Governance

  • Manage cross-functional teams (Data engineers, Data scientists, RPA developers).
  • Define KPIs, resource plans, budgets, and timelines for digital initiatives.
  • Manage vendor relationships and SLAs.
  • E. Infrastructure, Cloud, and Integration Oversight

  • Design and maintain scalable architecture for AI on Glenmark Azure Private cloud
  • Integrate digital tools with SAP ECC, SAP S / 4 HANA, eBMR, LIMS, eCTD, Trackwise, IT Security SIEM systems.
  • Ensure high availability, fault tolerance, and disaster recovery for AI infrastructure platforms.
  • Check daily system health status of cloud-hosted models
  • Ensure backups, DR protocols, and Log retention are operating correctly
  • F. Training awareness, User / Stakeholder Adoption & Documentation

  • Training awareness sessions, user / stakeholder adoption
  • Ensure proper documentation of all activities (service / projects) are maintained.
  • Perform system validation activities, including creating and executing test scripts, generating validation documentation, and ensuring compliance with regulatory requirements (such as FDA 21 CFR Part 11 / MHRA / EU Annex 11) as applicable for R&D, Regulatory, Manufacturing / Quality area
  • KEY RELATIONSHIPS / STAKEHOLDERS :

    External

    Principals / OEMS, Implementation Partners, Consultants, Vendors, Certification bodies and External auditors / agencies

    Internal (other than Direct Reports)

    Vice President IT, Sr. General Manager Information Technology, Business Heads (Domestic as well as Global locations), Functional and Departmental heads, All subordinates in concerned areas and span of control

    DESIRED EXPERIENCE AND KNOWLEDGE

    Educational Qualifications

     Bachelor's in Engineering / Computer Science / IT

     Master's degree (MBA, M.Tech, or MS in Data Science / AI) preferred.

    Experience

     12–15 years of progressive experience in IT, with at least 3 - 5 years in leadership roles in any Industry vertical

     Proven experience leading AI, RPA, and data analytics transformation at scale

    Knowledge and Skills (Functional / Technical)

     Strong grasp of Data science tools, Statistical modelling, and AI / ML frameworks

     Expertise in RPA tools and automation architecture.

     Experience with cloud-native analytics and data engineering platforms.

     Proven Integration experience and supporting IT systems across any Industry vertical

     Knowledge of system validation methodologies

     Familiarity with data integrity and data governance principles specific to pharmaceutical manufacturing and quality.

     Vendor management

     Proficiency in IT infrastructure, networking, and security principles within a manufacturing environment.

    Behavioural Attributes

     Communication and interpersonal skills

     Problem solving and analytical thinking

     Flexible & Adaptive to different working environments

     Project and team management skills

     Innovative approach

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