Top Data & Analytics Jobs in Indianapolis, IN

Lead GRS Data & Analytics business insights strategy and delivery: own executive reporting, drive MDM adoption, build shared BI/MI capabilities, ensure trusted governed reporting, partner with business and data teams, and lead a cross-functional insights organization to increase adoption and data-driven decision making.

Interns will solve client business problems by leveraging analytics and research, designing custom analyses, and communicating results effectively.

The Senior Data Analyst will lead analytics projects, translate complex data into insights, and support product strategies across various teams, ensuring data-driven decision making.

The Senior Data Analyst for Payments will analyze and optimize payment processes, collaborate with cross-functional teams, and ensure regulatory compliance to improve financial operations.

As a Data Analyst at Doximity, you will analyze extensive datasets, work with cross-functional teams, create analytics, and inform data strategies to enhance healthcare solutions.

The Data Program Associate/Manager will identify data acquisition opportunities, collaborate with product teams on datasets, and build AI systems for data improvement.

Lead end-to-end data science initiatives: design, deploy, and monitor production ML models for credit risk, pricing, collections, and fraud. Partner cross-functionally to integrate models, set development standards, mentor team members, and maintain reliable, scalable machine learning pipelines and monitoring systems.

As a People Team Data Analyst, you'll analyze hiring data to influence recruitment strategies and improve hiring processes, ensuring high data quality and effective communication of insights.

Lead client engagements delivering advanced reporting, analytics, and large-scale historical data migrations into Unanet ERP AE. Design and validate complex SQL, SSRS, and Power BI solutions, mentor junior consultants, use AI-assisted tools for analysis and QA, and manage multiple projects to ensure accurate reconciliation and client outcomes.

Lead design and implementation of scalable, HIPAA-compliant data pipelines and platforms for healthcare ML. Build ETL, orchestration, and tooling for processing EHR, claims, pharmacy, and bioinformatics data; collaborate with data scientists to produce modeling-ready datasets and ensure data quality, reliability, and operational excellence.