AI Scientific Business Analyst for Drug Development

Falcon Smart IT (FalconSmartIT)

San Mateo (CA)

On-site

USD 140,000 - 190,000

Full time

33 hours ago

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Job summary

Falcon Smart IT seeks an AI Scientific Business Analyst to blend life sciences expertise with business analysis and AI product delivery. You will partner with Product Managers, AI engineers, and data teams to define AI use cases for clinical research and drug development.

The ideal candidate has a strong scientific background, deep knowledge of clinical development, and can translate complex needs into structured AI requirements that enable successful product delivery.

Qualifications

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 and Clinical Development.
Experience in Translational Science and Oncology or related therapeutic areas.
Strong understanding of the clinical development lifecycle and pharmaceutical development processes.
8+ years of experience in 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 outcomes.
Strong written and verbal communication skills; self-driven and independent.
Experience managing UAT activities and stakeholder communication.

Responsibilities

Define AI use cases, including problem framing, success criteria, and measurable outcomes.
Translate business needs into AI-ready requirements, including model outputs and user interaction patterns.
Ensure AI use cases reflect scientific intent and business objectives with acceptance criteria.
Act as bridge between business needs and technical feasibility; align stakeholders.
Lead requirements refinement, state analyses, documentation, prioritization, and feasibility checks.
Document user, functional and AI-specific requirements with data inputs and outputs.
Own UAT planning, execution, and test cycle coordination; drive release readiness.
Maintain user stories and acceptance criteria in Jira/ADO; produce URS/FRS when required.
Produce current/future state artifacts to support solution design.
Lead data specs, source-to-target mappings, and AI input/output definitions with Data/AI teams.