Manager, Evidence Generation AI & Digital Lead

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Job Description:

Role Objectives:

Coordinate AI-enabled surveillance, supporting continuous or periodic monitoring of internal and external scientific evidence relevant to products, therapeutic areas, launches, competitors, evidence gaps, and defined scientific questions. Operate AI-assisted alerts, monitoring feeds, filtering, output logs, and handoffs to enable and support the Global Evidence Generation teams on evidence relevance decisions, scientific interpretation, follow-up actions, and decisions on whether outputs inform IEPs, content updates, or further analyses.

Key Responsibilities:

AI-enabled Surveillance Operations:

• Configure AI-enabled alerts, monitoring feeds, and search criteria based on Global Evidence Generation-defined scope, search focus, business triggers, cadence, and inclusion / exclusion logic
• Run automated surveillance on defined schedules and monitor feed completeness, technical errors, duplicate outputs, and predefined exclusion criteria following all protocols and guardrails
• Filter surveillance results for duplicates, formatting issues, technical errors, and clearly non-relevant outputs based on defined rules
• Route potentially relevant outputs to US evidence owners for relevance review and follow-up decisions
  
  

Output Logging & Traceability:

• Log surveillance outputs, routing decisions, evidence owner responses, follow-up decisions, and surveillance history
• Maintain source links, search strings, alert parameters, monitoring cadence, inclusion / exclusion rules, and output versions
• Maintain reviewed outputs and decision rationale to support traceability and future reuse
• Track unresolved items, overdue reviews, recurring technical issues, and gaps in search criteria
  
  

Stakeholder Coordination & Escalation:

• Coordinate with Global Evidence Generation, RWD CoE, Scientific Communications, DD&T, I&A, and other partners to ensure surveillance outputs are routed appropriately
• Escalate unclear relevance, high-impact evidence signals, AI tool errors, recurring false positives / negatives, and surveillance scope issues to US owners
• Support continuous improvement of alert configuration, search logic, templates, and surveillance dashboards
  
  

Qualifications:

Experience :>2 years of related work experience; >2 years of experience in the biopharmaceutical industry; experience in medical affairs, evidence generation, literature surveillance, medical information, scientific communications, HEOR / RWE operations, or AI-enabled workflow coordination preferred

Technical skills:

• Working knowledge of biomedical literature databases, evidence surveillance, search strategy basics, and literature screening workflows.
• Familiarity with AI-assisted monitoring tools, automated alerts, filtering logic, output logs, and human review checkpoints
• Ability to maintain traceable records of search criteria, output routing, review decisions, and follow-up actions
• Strong attention to detail and ability to distinguish operational filtering from scientific relevance decisions
• Familiarity with PubMed, Embase, scientific databases, evidence repositories, dashboard tools, or AI-enabled literature tools preferred
  
  

Education: A scientific, medical, life sciences, pharmacy, public health, epidemiology, library science, or health economics degree is required

Languages: Fluent English required; additional languages advantageous

Locations:

IND - Bengaluru

Worker Type:

Employee

Worker Sub-Type:

Regular

Time Type:

Full time