Top Data & Analytics Jobs in Indianapolis, IN

Lead end-to-end web and mobile analytics: design and implement tagging strategies, ensure data quality, build data pipelines and dashboards, analyze user behavior, and provide actionable insights to Product, Marketing, and Engineering stakeholders.

The Finance Expert will enhance AI models by providing data annotations related to fixed income markets and collaborate with technical teams to improve model performance.

Lead content programming through analysis, classification, and editorial judgment. Monitor performance, synthesize query analysis, propose product improvements, curate content, and collaborate with Engineering/Data Science on LLM/ML/NLP initiatives.

The Business Intelligence and Analytics Manager is responsible for developing and improving the reporting environment using Microsoft Power BI, ensuring alignment with business needs, and providing insights for decision making.

The Azure Data Engineer will work with Azure Cost Management, advising on billing strategies, and managing large datasets for FinOps and analytics.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

The Analytics Manager analyzes complex datasets, builds models, conducts scenario analyses, and provides strategic recommendations to guide decision-making for leadership.

The Data Services Manager will oversee data movement and processing, ensuring accurate data for mail files, handling file conversions, data cleansing, and providing analytical reports. The role involves collaborating with clients and teams to troubleshoot and address data-related issues.

The Fraud & Risk Analyst will conduct investigations of suspicious activities, collaborate with various teams, and enhance fraud detection processes to protect clients and the company.

Analyze product and business data to define KPIs, build reliable analytics models and dashboards, and partner with cross-functional teams to surface insights, improve data quality, and support forecasting and experimentation.