Top Analytics Jobs in Indianapolis, IN

Leverage data analytics, business intelligence, and Python to deliver strategic insights and tailored solutions for clients. Build reports, dashboards, data pipelines, and support data architecture and quality initiatives. Analyze data from multiple sources to identify trends, improve operations, and inform decision-making. Collaborate with stakeholders and team members while continuously developing technical skills and contributing to process improvements.

Leverage data analytics, business intelligence, and data science techniques to deliver strategic insights and solutions for clients. Build reports, dashboards, data pipelines, visualizations, and data architecture using tools such as Oracle BI, QlikView, Spotfire, and BIRT. Ensure data quality, manage stakeholder relationships, improve analytics processes, interpret complex datasets, and mentor junior team members while contributing to client projects and business strategy.

The Clinical Data Associate will program and test clinical trial data collection systems, collaborate with data analytics teams, and enhance data management processes in trials.

Lead programmatic analytics for clients and internal teams by analyzing campaign and model performance, designing tests, developing measurement solutions, recommending optimizations, and presenting actionable insights. Partner with Sales, Customer Success, Product, Engineering, and clients to align marketing strategies, reporting requirements, and optimization efforts with business goals.

Leads the strategy, architecture, implementation, and evolution of enterprise analytics platforms. Responsibilities include designing scalable data platforms, integrating digital and enterprise data, establishing governance and security standards, optimizing analytics and BI capabilities, evaluating cloud technologies, managing platform performance and risks, and mentoring technical teams. The role also requires close collaboration with executives, clients, Product, Engineering, Data Science, Marketing, and business stakeholders.

Lead and scale Runpod’s analytics and business intelligence function, managing analysts and BI practitioners while setting the analytics roadmap. Own core company metrics, consumption and marketplace analytics, self-service reporting, experimentation practices, and executive and board-level insights. Partner with Product, Finance, Engineering, Security, Supply, and Go-to-Market leaders to improve data quality, modeling, decision-making, and strategic outcomes.

Build and own end-to-end data products, including pipelines, transformations, semantic models, dashboards, metrics, and AI-enabled workflows. Partner with business and technical stakeholders to turn ambiguous questions into trusted, maintainable solutions. Establish data quality testing, documentation, monitoring, and governance while improving architecture and automation. Use Snowflake, dbt, Power BI, and related technologies to support analytics across Marketing, Product, Finance, and Engineering.

Architect scalable data models and ELT pipelines using modern data lake technologies. Build self-service analytics products, establish enterprise data governance and observability standards, and lead data architecture across engineering teams. Partner with data scientists, product engineers, and business stakeholders to improve data literacy, identify root causes, and connect insights to business outcomes. Develop AI-enabled data tools and frameworks while providing technical leadership, mentorship, and direction for analytics engineering practices.

Design and maintain analytical data models, transformation frameworks, data-quality checks, semantic definitions, and metric consistency across analytics and customer-facing products. Partner with engineering, product, and analytics teams to document data, improve lineage, and enable trustworthy self-service data usage. The role requires advanced SQL, analytics engineering, dimensional modeling, testing, and collaborative translation of business concepts into precise data definitions.

Leads analytics for Pricing and Supply, managing a team of approximately eight analysts. Partners with cross-functional leaders to prioritize analytical work, build dashboards and decision frameworks, improve metric quality, and generate insights into pricing, supplier coverage, marketplace performance, conversion, margin, and customer behavior. Coaches analysts, establishes scalable analytics processes, and collaborates with data engineering teams to improve data models, tooling, and self-service capabilities.

Leads a 15+ person analytics organization supporting Growth, Sales, Marketing, and Finance. Owns the analytics strategy, operating model, metric governance, executive reporting, forecasting, experimentation, customer and revenue insights, and data foundation improvements. Partners with senior commercial and financial leaders to translate complex data into strategic recommendations and builds scalable processes, systems, and talent development programs.

Build AI-augmented BI dashboards, semantic layers, and AI-ready metadata. Use AI-assisted tools to accelerate SQL and dashboard development, productionize ML outputs into BI, enforce data quality and governance, and present insights to business stakeholders including C-suite.

Own end-to-end data products, including source onboarding, API and file-feed ingestion, orchestration, incremental and idempotent pipelines, Snowflake and dbt Cloud modeling, testing, documentation, alerting, and production reliability. Establish engineering standards, manage secrets and governance, use AI coding tools responsibly, collaborate with vendors and stakeholders, and mentor junior engineers.

Develop and maintain dashboards, reports, scorecards, KPI solutions, and analytical models that provide business performance insights. Responsibilities include trend and root-cause analysis, forecasting, data validation, stakeholder requirements gathering, reporting automation, process improvement, documentation, and data quality governance. The role partners with cross-functional teams and communicates findings to technical and non-technical audiences.

Build and maintain cloud cost monitoring, alerting, and optimization tooling. Develop automation, cost allocation/tagging, data pipelines, dashboards, and integrations with billing APIs. Support FinOps processes, implement cost guardrails, troubleshoot cost systems, participate in on-call rotation, and collaborate with senior engineers and product teams to drive cost-efficient infrastructure and reporting.

Lead revenue analytics by developing business cases, dashboards, KPI frameworks, experiments, and automated analytics solutions. Partner with client success, marketplace, merchants, and cross-functional teams to evaluate performance, guide go-to-market decisions, quantify product value, and scale data-driven execution. Serve as the analytics subject matter expert while translating structured and unstructured data into actionable recommendations and compelling stakeholder narratives.

Lead end-to-end analytics for major platform partnerships, identifying growth opportunities and informing product, investment, risk, and pricing decisions. Conduct complex analyses, design experiments, build scalable data models, metrics, dashboards, and AI-assisted workflows, and translate findings into business recommendations. Partner cross-functionally with Product, Engineering, Finance, Revenue, and Strategic Partnerships while mentoring analysts and improving analytical practices.

Lead end-to-end COGS and gross margin analysis for hardware and software products, model cost-saving scenarios, answer ambiguous executive questions, partner with data engineering/finance/product, build reliable datasets and analytical frameworks, and present recommendations to C-suite stakeholders.

Uses advanced healthcare analytics to identify member and client needs, evaluate programs, develop predictive models and segmentation criteria, measure clinical, utilization, and financial outcomes, and guide product innovation and business strategy. Partners with clinical and business leaders, conducts applied research, develops analytical methodologies, addresses data limitations, and communicates findings through reports, white papers, conferences, and publications.

Leads complex analytics initiatives and partners with business leaders to define problems, analyze pharmacy, sales, and operational data, and develop actionable recommendations. Manages engagements across the full analytics lifecycle, from discovery through solution delivery and implementation support. Designs metrics, dashboards, frameworks, and decision-support tools while communicating insights to executive, operational, and technical audiences. The role emphasizes consultative analytics and business problem solving rather than software development or data infrastructure engineering.

Own GTM performance analytics, KPI and target setting, reporting, forecasting, compensation planning, and performance reviews across Sales and Post-Sales. Identify anomalies and optimization opportunities involving conversion, churn, productivity, pricing, packaging, segmentation, channel economics, and customer quality. Partner with Finance and GTM leaders to develop recommendations, lead strategic initiatives, and ensure data integrity while translating analysis into actionable business decisions.

Leads advanced analytics strategy for Behavioral Health and Cost of Care programs. Directs research, evaluation, consulting, dashboards, and data-driven insights on cost, utilization, and program performance. Builds and manages an analytics team, partners with executives and cross-functional stakeholders, modernizes analytics capabilities, and supports actuarial forecasting through health economics and program-impact studies.

Lead a GTM Analytics team supporting Marketing, Sales, RevOps, and Customer Operations. Manage embedded analysts, establish trusted reporting and QA processes, review SQL and dashboards, guide funnel, campaign, sales, support, forecasting, segmentation, attribution, and experimentation analysis, and deliver executive recommendations. Partner with GTM leaders and data engineers, coach analysts, and develop self-service analytics, automation, governed dashboards, metric documentation, and AI-assisted workflows.

Leads the strategic direction of performance analytics and measurement for global enablement efforts. Owns the analytics roadmap, defines KPIs, develops AI-driven seller-readiness assessments, and partners with data engineering, sales, enablement, and technology teams. Translates complex analysis into executive-level insights, drives cross-functional alignment, and leads strategic measurement initiatives.

Leads a team of five experienced analysts and data scientists while personally owning strategic analytics across ecommerce, health, supply chain, inventory, fulfillment, and merchandising. Partners with executives, establishes KPI and reporting standards, prioritizes the analytics roadmap, and delivers actionable business insights. The role also advances AI-native, self-service analytics capabilities, strengthens data governance and quality, and builds a high-performing analytics culture.