Practice: Accenture S&C-; GN- Industry &

- Enterprise

Capability: Life Sciences –

- R&D; (General R&D;, Clinical, Safety &
- Regulatory)

Career Level: Consultant

Experience: 3-7 yrs

WHAT WE ARE LOOKING FOR

- AI Transformation Advisory: AI chance identification and qualification across Life Sciences R&D; functions
- AI-ready process design and solution shaping for drug discovery, clinical development, and regulatory workflows;

experience conducting client workshops and capability assessments in Life Sciences context

- Life Sciences R&D; Domain Expertise (AI fluent): Working knowledge of one or more Life Sciences R&D; sub-functions and their data: General R&D; (target identification, drug discovery, R&D; portfolio management, translational research)

- Clinical (protocol development, site selection, patient recruitment, clinical data management, EDC, CTMS, eTMF and other systems)
- Safety &
- Regulatory (pharmacovigilance, adverse event management, signal detection, regulatory submissions –
- IND/NDA/BLA/CTD, labeling, regulatory intelligence etc.)
- Process Excellence + AI (R&D;): Process discovery and redesign across R&D; sub-functions; business process modelling for clinical operations, regulatory submissions, and safety workflows; process analysis and optimization with knowledge of GxP compliance requirements and validation considerations
- Life Sciences R&D; Functional Transformation: Functional process knowledge across R&D; value chain – study start-up, clinical trial management, pharmacovigilance operations, regulatory affairs,



and medical writing; familiarity with key platforms such as Veeva Vault (CTMS, RIM, Safety, eTMF), Medidata Rave, Argus Safety etc.
- AI Value Architecture (R&D;): Value discovery and benefit quantification for AI initiatives in R&D; contexts (e.g. cycle time reduction in clinical trials, submission timelines, PV processing efficiency); business case development with understanding of R&D; cost drivers and regulatory risk dimensions
- Life Sciences R&D; Data &
- AI: Data readiness assessment for AI across R&D; data types (clinical trial data, ICSR/safety data, regulatory documents, scientific literature); understanding of data standards (CDISC –
- SDTM/ADaM, MedDRA, WHO Drug); data product concepts and AI adoption support in GxP-compliant environments
- Agentic Enterprise (R&D;): Identification and scoping of agentic AI opportunities across R&D; sub-functions; agent workflow mapping and orchestration design for multi-step R&D; processes; human-in-the-loop design with sensitivity to regulatory and patient safety considerations; knowledge of agentic frameworks and platforms (e.g. LangChain, Copilot Studio, AWS Bedrock Agents) and their applicability in Life Sciences contexts
- Across all: AI fluency (fundamentals of AI, GenAI, Agentic AI);

requirements definition; understanding of Life Sciences regulatory environment (FDA, EMA, ICH guidelines); consulting skills including structured problem-solving, stakeholder management, and ability to engage with both scientific and business audiences

📌 I&P GN - I&E - Life Science – R&D Consultant - Process Excellence-PE (Bengaluru)
🏢 Accenture in India
📍 Bengaluru