AI Scientific Business Analyst

Job Title: AI Scientific Business Analyst
Location: Remote
Job Type: Full-Time / Permanent
Salary: Up to $120,000 per year
Experience: 15+Years

Job Summary

We are seeking an experienced AI Scientific Business Analyst with a strong background in Life Sciences/Pharmaceutical R&D, Clinical Research, Clinical Development, and Business Analysis. The ideal candidate will bridge scientific/business requirements with AI product development, working closely with Product Managers, Business Leads, AI Engineers, Data Teams, and scientific stakeholders.

The candidate should have hands-on experience translating complex scientific and business problems into structured requirements, defining AI use cases, developing acceptance criteria, managing UAT, and supporting AI/ML and Generative AI initiatives within pharmaceutical R&D environments.

Please Note: Candidates from healthcare insurance or surgical manufacturing domains are not a fit for this position.

Primary / Mandatory Skills

• Data Statistics and Programming

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

• Strong experience in Clinical Research, Clinical Development, Translational Science, Oncology, or related therapeutic areas

• 8+ years of experience working within Pharmaceutical R&D organizations

• 8+ years of experience in Business Analysis and Requirements Gathering

• 5+ years of experience defining KPIs, success metrics, and measurable business outcomes

• Strong understanding of the clinical development lifecycle and pharmaceutical development processes

• Ability to translate ambiguous business problems into structured functional and AI-ready requirements

• Experience with UAT planning, execution, stakeholder communication, and release readiness

• Understanding of AI/ML concepts and Generative AI solutions

• Experience with AI products, analytics platforms, or intelligent automation

• Knowledge of Prompt Engineering, AI Agents, LLM-based workflows

• Agile/Scrum experience with Jira or Azure DevOps

• GxP / Computer System Validation (CSV) knowledge

• Basic SQL for data validation and analysis

• Basic Python for exploratory data analysis

Key Responsibilities

• Partner with Product Managers, Business Leads, AI Leads, and Data Leads to define AI use cases, success criteria, and measurable outcomes.

• Translate business and scientific needs into AI-ready requirements covering data inputs, model outputs, recommendations, workflows, prompts, and dashboards.

• Apply clinical research and pharmaceutical development knowledge to ensure AI solutions align with scientific and business objectives.

• Act as the bridge between business stakeholders and technical/AI teams.

• Perform current-state and future-state analysis, requirements refinement, prioritization, and feasibility alignment.

• Create user stories, functional requirements, AI requirements, and detailed acceptance criteria.

• Define AI input/output specifications and success metrics in collaboration with Data and AI teams.

• Develop and maintain requirements and user stories in Jira/Azure DevOps.

• Prepare URS/FRS, process flows, data flows, impact assessments, and source-to-target mappings as required.

• Plan and execute User Acceptance Testing (UAT), including test scenarios, test cases, defect tracking, retesting, and business sign-off.

• Partner with testing teams to ensure requirements are clear, testable, and aligned with expected system behavior.

• Provide regular status updates covering progress, risks, issues, dependencies, and decisions.

• Work collaboratively with scientists, clinicians, AI engineers, data teams, and product leadership.

Required Deliverables

• User Stories and Acceptance Criteria

• URS / FRS documentation

• Current-State and Future-State Process Flows

• Data Flows and Source-to-Target Mappings

• AI Input/Output Definitions

• KPI and Success Metric Definitions

• UAT Plans, Scenarios, and Test Cases

• UAT Defect Tracking and Retesting

• UAT Test Summary Reports

• Business Requirements and Functional Specifications

• Status, Risk, Issue, and Dependency Updates

AI / Technology Experience

• Understanding of Artificial Intelligence and Machine Learning concepts

• Generative AI and LLM-based applications

• Prompt Engineering

• AI Agents / Agentic AI workflows

• AI-powered analytics and intelligent automation

• Basic Python for exploratory analysis

• Basic SQL for data validation

• Jira / Azure DevOps

• Agile / Scrum methodologies

• GxP / CSV environments

Preferred Domain Experience

• Pharmaceutical R&D

• Clinical Research

• Clinical Development

• Drug Discovery

• Translational Science

• Oncology

• Life Sciences

• Biomedical Sciences

• Biotechnology

Communication & Interpersonal Skills

• Excellent written and verbal communication skills

• Strong stakeholder management and collaboration abilities

• Ability to communicate effectively with scientific and technical teams

• Strong analytical and problem-solving skills

• Self-driven and capable of working independently

• Ability to manage priorities in an Agile environment

• Strong interpersonal skills and ability to build productive relationships