Top Data & Analytics Jobs in Indianapolis, IN

Provides analytical support to Carrier and Sales Center teams by developing datasets, dashboards, KPIs, forecasting models, financial reports, and actionable business insights. Responsibilities include stakeholder requirements gathering, data modeling, SQL analysis, visualization, P&L reporting, performance tracking, and communicating recommendations to management. The role also supports strategic initiatives, operational improvements, and end-to-end analytics projects using BI tools.

The Sr. Data Modeler designs and implements data architectures, optimizes SQL queries, and develops data pipelines to support analytics initiatives ensuring scalability and alignment with business needs.

Leads web analytics strategy, GA4 and GTM implementations, tagging specifications, dashboards, reporting, experimentation, and data-quality monitoring. Analyzes user behavior, conversion funnels, feature adoption, and A/B test results to provide actionable recommendations for product and business decisions. Partners with product, engineering, UX, and business stakeholders and communicates analytical findings to technical and non-technical audiences.

Own marketing channel performance analysis, reporting, experimentation, dashboards, and measurement frameworks. Develop incrementality, LTV, and forecasting analyses; identify data quality risks; and translate complex findings into actionable recommendations for Marketing, Growth, and Finance stakeholders. The role requires strong SQL, BI reporting, marketing measurement, experimentation, and analytical communication skills, with AI tools used to accelerate analytics workflows.

Analyzes, validates, and maintains Army MEDCOM facilities and real property data; supports dashboards, reporting, data integration, quality assurance, process improvement, documentation, training, and stakeholder deliverables. The role identifies data discrepancies, develops recommendations, provides technical support, and assists with Medical Readiness and Facility Investment Plan requirements. Periodic travel to project sites, meetings, training, and data collection locations may be required.

Develop business intelligence and analytics solutions using financial, operational, RF, and video performance data. Build scalable data models, dashboards, reports, automation workflows, and ETL/ELT processes using Power BI, Tableau, DataMiner, and Qligent. Analyze trends and anomalies, monitor satellite and video delivery performance, translate business requirements into actionable insights, and collaborate with enterprise stakeholders in a fully remote consulting role.

Guide customers through data integration and migration, analyze data quality, identify and resolve anomalies, support validation and system synchronization, and document troubleshooting practices. The role communicates recurring data trends to product and engineering teams, improves operational processes, and enhances customer self-service. It requires professional QuickBooks experience, customer-facing technical support or onboarding experience, strong communication, and problem-solving skills.

Leads commercial business intelligence strategy, Power BI reporting, dashboards, analytics, data governance, CRM optimization, and sales process improvement. Manages two direct reports and partners with commercial, finance, and operational leaders to improve revenue performance, forecasting accuracy, data quality, and commercial effectiveness. Oversees sales incentive compensation analytics and cross-functional system transformation initiatives. The role is fully remote with 10% overnight travel.

Own B2B pipeline and B2C growth analytics, including attribution, acquisition, registration funnels, SEO performance, forecasting, dashboards, experimentation, and marketing measurement. Partner with marketing, growth, product, sales, and data engineering to establish reliable metrics, improve reporting, guide investment decisions, and communicate actionable insights. The role also contributes to dbt models, semantic layers, AI-assisted analytics, and analyst mentorship.

Designs and maintains scalable enterprise data pipelines, models, and data products supporting analytics, reporting, Power BI, AI agents, and machine learning. The role implements layered data architectures, ensures data quality and performance, integrates data across platforms, troubleshoots pipeline issues, and collaborates with architects, analysts, and product owners. AI-assisted development tools such as GitHub Copilot and Claude are used to build AI-ready data solutions.