Senior Business Analyst - AI Scientific - data statics and Programming

Key Responsibilities:

Individual contributor partner with Product Manager, Business Lead, AI Leads, and Data Lead to define AI use cases, including problem framing, success criteria, and measurable outcomes.
Translate business needs into AI-ready requirements, including:
Input data expectations
Model outputs (predictions, insights, recommendations)
User interaction patterns (e.g., workflows, prompts, dashboards)
Apply foundational knowledge of clinical research and drug development to ensure AI use cases, requirements, and acceptance criteria accurately reflect scientific intent and business objectives
Act as the primary bridge between "what's needed" (business) and "what's possible" (technical) to ensure stakeholder alignment.
Leads requirements refinement, including current/future state analysis, requirements documentation, prioritization, feasibility alignment and stakeholder alignment.
Document user, functional and AI-specific requirements including data inputs, model output, user interaction workflows with acceptance criteria aligned to business outcomes and system behavior.
Owns User Acceptance Testing planning and execution.
Partners with Testing team to ensure requirements are testable and the solution is ready for release.

Deliverables:

Update and maintain user stories and acceptance criteria in Jira/ADO.
Author formal User Requirements Specification (URS)/Functional Requirements Specification (FRS), when required
Partners with testing teams to ensure requirements are clear, unambiguous, and testable.
Produce current state and future state artifacts (process flows, data flows, impact summaries) as required to support solution design.
Lead or contribute to data specifications, source-to-target mappings, and AI input/output definitions in partnership with Data and AI teams
Develop User Acceptance Test (UAT) plan, scenarios, and test cases aligned to approved requirements.
Lead UAT, including coordination of test cycles, defect logging, and retesting.
Produce UAT test summary report supporting business acceptance and release readiness.
Provide regular status updates covering progress, risks, issues, and dependencies.
Document decisions, assumptions, and clarifications related to contracted scope.

Communication Skills:

Communicate effectively with internal and customer stakeholders
Communication approach: verbal, emails and instant messages

Interpersonal Skills:

Strong interpersonal skills to build and maintain productive relationships with team members
Provide constructive feedback during code reviews and be open to receiving feedback on your own code.

Problem-Solving and Analytical Thinking:

Capability to troubleshoot and resolve issues efficiently.
Analytical mindset

Task/ Work Updates

Prior experience in working on Agile/Scrum projects with exposure to tools like Jira/Azure DevOps
Provides regular updates, proactive and due diligent to carry out responsibilities
Successfully understand business priorities, clinical workflows, and AI product roadmap.
Partner with stakeholders to define and document high-quality AI use cases and requirements.
Deliver complete business analysis artifacts including User Stories, URS/FRS, process flows, and acceptance criteria.
Establish clear AI input/output definitions and success metrics for prioritized initiatives.
Successfully lead User Acceptance Testing and support multiple AI solution releases.
Improve collaboration between scientific stakeholders and AI engineering teams, reducing requirement ambiguity and delivery delays.
Contribute to the successful rollout of AI capabilities supporting clinical development and drug discovery initiatives.
Become a trusted business partner for AI-enabled scientific product development.

Understanding of AI/ML concepts and Generative AI solutions

Experience with AI products, analytics platforms, or intelligent automation initiatives
Knowledge of prompt engineering, AI agents, or LLM-based workflows
Experience working in Agile and iterative product delivery
GxP / Computer System Validation (CSV) knowledge
Basic SQL for data validation and analysis
Basic Python for exploratory data analysis
Familiarity with Jira or Azure DevOps

Work at the intersection of AI and Life Sciences, shaping the future of drug discovery and clinical development.

Partner with multidisciplinary teams including scientists, clinicians, AI engineers, and product leaders.
Contribute to cutting-edge Generative AI and Agentic AI initiatives with real-world impact in healthcare.
Gain exposure to modern AI technologies, data platforms, and cloud-based AI ecosystems.
Be part of a collaborative, innovation-driven environment that encourages continuous learning and professional growth.
Play a key role in delivering AI solutions that accelerate research, improve decision-making, and enhance patient outcomes.
Opportunity to influence the next generation of AI-powered scientific products within a global pharmaceutical ecosystem.
 Partner with multidisciplinary teams including scientists, clinicians, AI engineers, and product leaders.
Contribute to cutting-edge Generative AI and Agentic AI initiatives with real-world impact in healthcare.
Gain exposure to modern AI technologies, data platforms, and cloud-based AI ecosystems.
Be part of a collaborative, innovation-driven environment that encourages continuous learning and professional growth.
Play a key role in delivering AI solutions that accelerate research, improve decision-making, and enhance patient outcomes.
Opportunity to influence the next generation of AI-powered scientific products within a global pharmaceutical ecosystem.