WE’RE HIRING: Business Analyst – Data & AI (Life Sciences / Pharma R&D)
Job Title: Business Analyst-Data & AI
Location:
100% Remote / Work From Home
Employment Type:
Full-Time / Direct-Hire
We are seeking an experienced Business Analyst who bridges the gap between Life Sciences, Data Science, and AI. In this role, you will partner with Product Managers, Business Leads, and AI/Data Engineers to define and deliver cutting-edge, AI-powered solutions supporting clinical research and drug development.
Key Responsibilities
Translate Business Needs into AI Requirements:
Define input data expectations, model outputs (predictions, insights, recommendations), and user interaction workflows (prompts, dashboards, agentic workflows).
Cross-Functional Collaboration:
Serve as the primary bridge between business leads and technical AI/Data teams to define use cases, problem framing, and measurable outcomes.
Domain Alignment:
Apply foundational knowledge of clinical development, translational science, or oncology to ensure AI outputs align with scientific intent.
Agile Requirements & Documentation:
Author User Stories, Acceptance Criteria, and formal URS/FRS documents in Jira/Azure DevOps.
UAT Leadership:
Own end-to-end User Acceptance Testing (UAT)—from planning and scenario creation to defect tracking and final sign-off.
What We’re Looking For
8+ years
of Business Analysis experience within Pharmaceutical R&D, Clinical Development, Biotech, or related life science domains.
5+ years
defining KPIs, success metrics, data statistics, and measurable business outcomes.
Strong understanding of the
Clinical Development Lifecycle
paired with recent
AI / Gen AI
exposure.
Educational Background:
Bachelor’s or Master’s degree in Life Sciences, Biotechnology, Health Sciences, Pharmacy, or Biomedical Engineering.
Demonstrated hands-on experience leading
UAT planning, execution, and stakeholder communication
on Agile/Scrum projects.
Good-to-Have / Secondary Skills
Understanding of Gen AI concepts (prompt engineering, AI agents, LLM workflows).
Basic
Python
for exploratory data analysis &
SQL
for data validation.
Knowledge of
GxP
/ Computer System Validation (CSV) protocols.