Top Remote Data & Analytics Jobs in Indianapolis, IN

Own commercial and growth analytics for GeneDx’s top line, answering questions about volume, revenue, pricing, coverage, field capacity, and product performance. Serve as a senior advisor to commercial and product leaders, structure ambiguous problems, lead analyses end to end using AI agents, communicate executive-ready insights, support evidence-based decisions, monitor outcomes, and surface emerging opportunities. Maintain analytical governance, apply measurement and experimental design, and contribute reusable methods to the analytics function.

Leads operational analytics for the Take 5 Oil Change network, translating transactional and market data into insights that improve sales, profits, volume, and shop performance. Responsibilities include complex analysis, KPI reporting, dashboards, executive presentations, operational initiative measurement, stakeholder collaboration, data-quality improvement, and mentoring analysts. The role requires strong Excel, SQL, financial modeling, communication, and multi-shop operations experience.

Supports medical education evaluation and grant-seeking through data manipulation, statistical analysis, reporting, visualization, and stakeholder communication. The role prepares reports, presentations, conference abstracts, and publications using Excel, R, SPSS, SAS, and related tools. It also explores open-ended evaluation questions, manages multiple projects, and applies generative AI to accelerate report drafting, data validation, formatting, and deliverable quality assurance.

Manages enterprise data governance and privacy compliance programs, including GDPR and CCPA adherence, data subject rights processes, governance controls, privacy documentation, compliance metrics, and continuous improvement. Coordinates with business, legal, compliance, security, and technology stakeholders; maintains process documentation; monitors risks and response timelines; supports automation, reporting, awareness training, and audit readiness across global operating units.

Lead marketing analytics: own reporting frameworks, dashboards, and data quality; monitor KPIs; run A/B tests and experiments; build attribution, forecasting, segmentation, and budget-allocation models; automate workflows and drive continuous measurement improvements.

Own advanced analytics for Airbnb product teams, using large datasets, statistical modeling, experimentation, causal methods, forecasting, and metrics development to guide product and business decisions. Build reporting and analytical tools, collaborate cross-functionally, automate repetitive work with AI, and present actionable insights to senior stakeholders. The role supports Guest App or API initiatives, including promotions and marketplace optimization.

Leads enterprise Business Intelligence strategy, architecture, governance, security, and self-service analytics adoption. Architects solutions across Power BI, Tableau, SAP BusinessObjects, and Databricks; establishes semantic models, data standards, DevOps, CI/CD, and reporting performance practices. Partners with executives and technical teams to modernize analytics platforms, reduce manual reporting, and enable AI-ready decision-making. Mentors BI professionals and drives enterprise data literacy and analytics transformation.

Analyze market and live data to set dynamic ticket prices using Uptick, build strategic pricing recommendations, communicate with clients about strategy and performance, and collaborate with BI and engineering to improve product performance.

Analyze healthcare operations data to identify bottlenecks, model advocate capacity and supply-demand, build scalable Hex dashboards, refine SQL and dbt data transformations, and translate complex findings into operational recommendations. The role partners with Operations, Engineering, Product, Marketing, and Finance to improve workflows, reporting, resource allocation, and business outcomes across the patient and advocate journey.

Leads LTK’s Data Engineering team, owning technical direction, architecture, pipelines, data products, governance, quality, reliability, and platform modernization. Manages and develops engineers, drives roadmaps and complex initiatives, partners with cross-functional stakeholders, and balances scalability, security, performance, cost, and business priorities. Establishes engineering standards, improves operational practices, manages risks and dependencies, and builds trusted, reusable data capabilities supporting analytics, reporting, products, and AI use cases.