BA with Pharma and Ai

Falcon Smart IT (FalconSmartIT); San Mateo (CA); Presencial; USD 150.000 - 190.000; Jornada completa

Descripción de la vacante

Falcon Smart IT (FalconSmartIT) is seeking an AI Scientific Business Analyst with life sciences expertise to translate complex clinical needs into AI-driven product requirements. You will collaborate with Product Managers, AI Engineers, and Data teams to define measurable outcomes and ensure successful delivery.

The role emphasizes strong communication, independent work, and governance of UAT activities within a fast-paced pharmaceutical environment.

Formación

• 8+ years of experience in pharmaceutical R&D
• 8+ years of excellent business analysis and requirements gathering
• 5+ years of defining KPIs and measurable business outcomes
• Strong written and verbal communication skills
• Self-driven with ability to work independently
• Experience managing UAT activities and stakeholder communication

Responsabilidades

• Partner with Product Manager, AI Leads and Data Lead to define AI use cases and success criteria
• Translate business needs into AI-ready requirements and acceptance criteria
• Document data inputs, model outputs and user interaction workflows
• Lead requirements refinement and stakeholder alignment
• Own UAT planning, testing and defect retesting
• Produce URS/FRS documents when required
• Maintain user stories and acceptance criteria in Jira/ADO
• Produce current and future state process/data flow artifacts

Conocimientos

Business analysis

Requirements gathering

KPIs and metrics

Communication

UAT management

Self-motivation

Educación

Bachelor's or Master's in Life Sciences/related

Herramientas

Jira

Azure DevOps

Descripción del empleo

We are looking for an AI Scientific Business Analyst who combines life sciences expertise with business analysis and AI product delivery. This role will partner with Product Managers, Business Leads, AI Engineers, and Data teams to define and deliver AI-powered solutions that support clinical research and drug development. The ideal candidate has a strong scientific background, understands clinical development processes, and can translate complex business needs into structured AI requirements that enable successful product delivery.

Primary (Must have) Skills

Bachelor's or Master's degree in Life Sciences, Health Sciences, Pharmacy, Biotechnology, Biomedical Sciences, or related discipline

Academic or professional experience in:

• Clinical Research
• Clinical Development
• Translational Science
• Oncology or related therapeutic areas
• Strong understanding of clinical development lifecycle and pharmaceutical development processes.
• 8+ years of Experience working within pharmaceutical R&D organizations.
• 8+ years of Excellent business analysis and requirements gathering skills.
• Ability to convert ambiguous business problems into structured functional requirements.
• 5+ years of Experience defining KPIs, success metrics, and measurable business outcomes.
• Strong written and verbal communication skills.
• Self-driven with ability to work independently.
• Experience managing UAT activities and stakeholder communication.

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:
• 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.
• 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.