Specialist, Business Analyst – AI Content Creation (Content Creation & Storage)

MSD Animal Health · Bengaluru

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Job Description

Specialist, Business Analyst – AI Content Creation (Content Creation & Storage)

The Opportunity

• Based in Hyderabad, join a global healthcare biopharma company and be part of a 130- year legacy of success backed by ethical integrity, forward momentum, and an inspiring mission to achieve new milestones in global healthcare.
• Be part of an organization driven by digital technology and data-backed approaches that support a diversified portfolio of prescription medicines, vaccines, and animal health products.
• Drive innovation and execution excellence. Be a part of a team with passion for using data, analytics, and insights to drive decision-making, and which creates custom software, allowing us to tackle some of the world's greatest health threats.

Our Technology Centers focus on creating a space where teams can come together to deliver business solutions that save and improve lives. An integral part of our company’s IT operating model, Tech Centers are globally distributed locations where each IT division has employees to enable our digital transformation journey and drive business outcomes. These locations, in addition to the other sites, are essential to supporting our business and strategy.

A focused group of leaders in each Tech Center helps to ensure we can manage and improve each location, from investing in growth, success, and well-being of our people, to making sure colleagues from each IT division feel a sense of belonging to managing critical emergencies. And together, we must leverage the strength of our team to collaborate globally to optimize connections and share best practices across the Tech Centers.

About Digital Human Health (DHH) 

Digital Human Health (DHH) connects technology, data, and people to enable and accelerate Human Health business across global markets. DHH supports commercial and medical teams by delivering customer-centric digital platforms, data capabilities, and technology-enabled operating models that enable flexible go-to-market approaches, actionable insights, and personalized customer experiences in a regulated environment. 

Within DHH, the Content Creation & Storage pillar of Digital Content & Customer Experience (DCCE) builds the platforms and capabilities that help Human Health create compliant, on-brand content faster. As part of the Content Accelerator, the pillar is moving content creation from manual production to AI-generated content that is built to brand and compliance standards from the start, combining agentic content creation platform, Adobe capabilities (including Adobe Brand Intelligence and Adobe Firefly), design system, and AEM/DAM foundations. 

Role Purpose 

Act as hands-on business and product partner for AI-enabled content creation, working closely with business users and vendor teams to shape, test, and evolve GenAI and agentic capabilities, and building the internal knowledge needed to confidently own custom components as the platform landscape evolves. 

Scope of Ownership & Adjacent Responsibilities 

• Support the AI Content creation workstream: experiment design, requirements, testing, and assessment of where Adobe capabilities can replace or complement custom-built components. 

• Build working ownership of custom agentic components. Understand how they work, maintain requirements and backlog, and guide their evolution with engineering and vendor teams. 

• Support the Adobe Firefly rollout across Human Health: access and onboarding inputs, playbook and enablement content, usage reporting, and user feedback loops. 

• Work closely with content creators, brand teams, and reviewers to capture real feedback, prioritize the most important items, and turn them into fast, practical iterations. 

• Flex across adjacent workstreams in the pillar (e.g., design system, guardrails/rules, AEM/DAM) as priorities shift. 

Key Responsibilities 

Business Analysis & Product Ownership Support 

• Translate business and workflow needs into clear requirements, user stories, and acceptance criteria for AI-enabled content creation capabilities. 

• Maintain and prioritize backlogs in partnership with the Product Owner; support sprint planning, refinement, and release readiness. 

• Map current-state and future-state content creation workflows, identifying where AI and agents add value and where human review remains essential. 

• Facilitate UAT with business, brand, and compliance stakeholders; track defects, gaps, and fixes through to closure. 

Hands-on GenAI & Agentic Delivery (Embedded with the Business) 

• Work hands-on with GenAI and agentic tools to test, configure, and validate capabilities (e.g., prompts, agent inputs/outputs, brand rules, assembly and validation steps). 

• Sit close to business users during pilots and early rollout: observe real usage, unblock issues quickly, and feed priority learnings back into the backlog. 

• Design and run structured experiments with clear scope, success criteria, test assets, and results (e.g., accuracy, false-flag rate, turnaround time, rework). 

• Build a working understanding of component architecture, integrations, and APIs to have informed discussions with engineering and vendors. 

Platform & Vendor Collaboration (Adobe and Partners) 

• Serve as a day-to-day contact for Adobe and implementation partners on ABI and Firefly: align on scope, prerequisites, dependencies, and timelines. 

• Assess build vs. buy trade-offs for components (custom vs. platform capability) and document recommendations with risks and dependencies. 

• Review vendor deliverables (playbooks, guides, configurations) to confirm fit needs and governance. 

Documentation, Governance & Communication 

• Maintain a clear source of truth (e.g., Confluence, JIRA) covering requirements, decisions, test results, and component documentation. 

• Embed compliance-by-design: human-in-the-loop controls, AI labeling, auditability, and alignment with AI and content policies. 

• Prepare crisp updates, MoMs, and decision summaries for leadership and cross-functional stakeholders. 

What Success Looks Like 

• We have internal capability to understand, maintain, and evolve custom content creation components with reduced dependence on vendors. 

• ABI experiments run to plan with clear results that support evidence-based platform decisions. 

• Firefly adoption grows across Human Health with users onboarded, enabled, and supported within guardrails. 

• Business feedback turns into prioritized improvements quickly, with visible gains in turnaround time, rework, and first-time-right content. 

• Requirements, decisions, and component documentation are current, traceable, and reusable. 

Qualifications & Experience 

Education 

Bachelor’s degree required; master’s degree preferred. 

Experience 

• 4–5+ years of experience as a Business Analyst, Product Analyst, Product Manager/Owner, or similar role in digital products or technology delivery. 

• Hands-on experience with GenAI tools or solutions, e.g., building, configuring, or testing prompts, AI workflows, agents, or LLM-based applications—beyond awareness level. 

• Exposure to agentic AI concepts (agents, orchestration, tool use, human-in-the-loop) and practical experience in pilots, proofs of concept, or early rollouts. 

• Experience working directly with business users in a delivery-embedded or customer-facing role, turning feedback into rapid iterations. 

• Strong requirements, user story, and process mapping skills; experience in Agile/Scrum with tools such as JIRA and Confluence. 

• Working technical literacy: APIs, integrations, data inputs/outputs, and the ability to engage credibly with engineers and vendors. 

• Excellent written and verbal communication; ability to work across a geographically distributed team (India, Europe, US). 

Preferred / Nice to Have 

• Experience with Adobe content ecosystem (Firefly, GenStudio, Express, AEM Assets, Workfront) or similar marketing/content technology. 

• Familiarity with design systems or Figma-based creative workflows. 

• Experience in pharma or other regulated environments; awareness of MLR/content review and AI governance considerations. 

• Experience with prompt engineering, basic scripting (e.g., Python), or low-code/AI agent builders. 

Key Competencies 

• Business-first problem solving with a bias for hands-on delivery 

• Ownership and learning agility in fast-changing AI platforms 

• Clear, concise communication and decision-ready documentation 

• Collaboration across business, engineering, and vendor partners 

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