Top Data & Analytics Jobs in Indianapolis, IN

The Director, Product Analytics & Strategy will lead market expansion, define product strategy, analyze market opportunities, and drive cross-functional collaboration to shape product direction and company growth.

The Lead Business Intelligence Analyst will modernize reporting frameworks using Adobe Analytics and Power BI, translating complex marketing data into insights and driving strategic decision-making through effective communication with stakeholders.

The role involves optimizing and managing Salesforce operations for various departments, driving Quote-to-Cash processes, and ensuring compliance while collaborating with other teams.

Lead and grow a casino analytics team to measure, diagnose, and optimize Casino revenue performance. Provide strategic analytics support to Revenue Operations, run deep-dive customer and promotion analyses, build scalable monitoring/alerting frameworks, translate insights into actionable recommendations, and manage an analytics roadmap prioritizing short-term wins and long-term AI-enabled strategies.

As a Lead Product Data Analyst, you'll drive data-informed decision-making across teams, develop data products, collaborate on metrics, and influence product strategies.

The Data Engineer will build real-time data pipelines for pricing algorithms, collaborate with teams, and contribute to batch data workflows.

As a Data Engineer II, you will build and optimize data pipelines in Databricks, ensure high-quality data delivery, and support generative AI applications. You will collaborate with data scientists and AI engineers to provide reliable data infrastructures and meet business needs.

The Business Analyst will manage the Quote-to-Cash lifecycle, liaising between IT and functional teams, and ensuring successful implementation of system updates while documenting requirements.

The Credit Bureau Business Analyst will manage bureau execution and analysis, support product onboarding and compliance controls, and drive data quality improvements through data analysis and cross-functional collaboration.

Support sales intelligence by collecting, preparing, and analyzing sales and marketing data; maintain dashboards and data quality; run pipeline and win/loss analyses; translate findings into clear visualizations and reports for stakeholders.