Senior Data Analyst III

Elsevier•New York, NY

4d•$104,900 - $209,700•Remote

About The Position

Elsevier is seeking a motivated Senior Data Analyst III to join their dynamic generative AI evaluation team. This role focuses on assessing and validating AI models that support healthcare decision-making tools, ensuring they meet rigorous standards for accuracy, fairness, and clinical relevance. The successful candidate will evaluate model performance, analyze output quality, and ensure AI solutions align with healthcare best practices. This position involves collaborating with cross-functional teams including AI researchers, product managers, clinicians, and engineers to evaluate AI models, analyze their outputs, and improve their performance in healthcare contexts.

Requirements

6-9 years of relevant experience in data analytics
Bachelor's degree required, Master's or PhD preferred in Mathematics/Science
Demonstrated thought leadership in analytics strategy and enterprise-wide project implementation
Have experience in a data analytics role
Have expertise in creating evaluation frameworks
Have expertise in using and querying relational database management systems such as Microsoft SQL Server, Snowflake or postgreSQL
Have expertise in using BI tools such as Tableau or PowerBI
Be able to demonstrate experience using Python for analysis

Responsibilities

Leading requirements gathering and development of analytics frameworks for evaluating generative AI models in healthcare applications
Leading and defining the strategic direction for AI evaluation methodologies in their product area
Managing the analytics roadmap for model evaluation. Collaborating with internal and external stakeholders to manage evaluation timelines and deliverables
Defining, developing, and deploying queries and metrics to assess AI model performance and output quality
Leading data model creation and maintenance for AI evaluation frameworks and monitoring systems
Conducting comprehensive QA of AI outputs and participating in risk analysis and mitigation
Understanding how security and privacy laws such as HIPAA affect AI deployment in healthcare. Understanding how to handle sensitive data including PHI and PII in AI contexts