Business Analyst, AI & Enterprise Data Products

Required Qualifications

• 7+ years of business analysis experience, including at least one delivery involving analytics, machine learning, or data-intensive applications.
• Working SQL proficiency — able to independently profile data, validate assumptions, and investigate discrepancies without waiting on an engineer.
• Demonstrated ability to write requirements and acceptance criteria for systems with non-deterministic outputs.
• Practical understanding of data modeling, source-to-target mapping, and integration patterns.
• Foundational understanding of machine learning concepts: training vs. inference, evaluation metrics and their tradeoffs, overfitting, drift, and the distinction between correlation and causation in model outputs.
• Experience in pharmaceutical, biotech, medical device, or another FDA-regulated industry.
• Experience validating or supporting a GxP-relevant AI/ML system, or familiarity with GAMP 5 Second Edition guidance on AI/ML.

Preferred Qualifications

• Familiarity with generative AI patterns where applicable: retrieval-augmented generation, prompt design, embedding and vector search, evaluation of open-ended outputs, and hallucination mitigation.
• Familiarity with predictive ML patterns where applicable: classification and regression, feature definition, class imbalance, and threshold tuning against business cost of false positives vs. false negatives.
• Hands-on exposure to modern data platforms: Snowflake, Databricks, Azure Synapse, dbt, or equivalent.
• Experience with enterprise source systems common in life sciences — Veeva Vault, SAP, LIMS, MES, TrackWise, Salesforce, ServiceNow.
• Familiarity with data governance tooling and concepts: catalogs, data contracts, stewardship models, lineage tracking.
• Working knowledge of HIPAA, GDPR, and PHI/PII de-identification practices.
• Certification such as IIBA CBAP/CCBA, PMI-PBA, CSPO, or a recognized data/AI credential.