Top Remote Analysis Reporting Jobs in Indianapolis, IN

The EDI Systems Analyst II collaborates with business units to manage EDI requirements, analyze processes, ensure compliance, and communicate project priorities. They lead requirement gathering sessions and improve workflows while partnering with developers.

The Clinical Research Lead oversees the execution of clinical trials by engaging investigators, managing sites, and optimizing enrollment strategies in the Oncology field.

The Director will oversee data governance, optimize audience engagement, and develop revenue-focused strategies while managing cross-department initiatives.

Lead multiple research verticals focused on civic data management, enhance data quality, implement workflows, and manage project execution while fostering team collaboration and development.

The Senior Actuarial Analyst conducts actuarial work for ratemaking and reserving, collaborates with teams, completes pricing assignments, and enhances data solutions while supporting innovation and regulatory compliance.

Lead and scale advertising analytics and tooling to optimize paid-media performance and incrementality. Build predictive and prescriptive models (forecasting, pacing, bidding, attribution), enable automation and self-service insights, and partner cross-functionally to align ad strategy with business goals while coaching a high-performing analytics team.

The Staff Analyst will analyze marketplace performance using advanced analytics, develop predictive models, and mentor junior analysts to enhance user experiences and operational efficiency.

The Data Infrastructure Engineer will centralize data capabilities, improve data pipeline architecture, and ensure efficient data access across teams while optimizing GCP usage.

Design, develop, and maintain SSRS and Sigma reports and dashboards; write and optimize SQL; collaborate with data warehouse team; document BI tools; unit test and troubleshoot reports; manage projects independently.

Lead end-to-end design, development, and deployment of ML models (churn, retention, LTV), drive causal inference and experimentation for targeting and bidding, partner with Product and Engineering to define metrics, instrument experiments, operationalize models, and mentor analytics teams to influence product roadmaps and personalized customer journeys.