Top Remote Analytics Jobs in Indianapolis, IN

Lead credit underwriting, pricing, verification, and portfolio performance for personal loans. Use data and ML/AI to design automated decisioning, manage credit/fraud risk, forecast losses, and present strategies to leadership and investors. Collaborate cross-functionally and build vendor/alternative-data strategies to drive profitable growth while keeping losses within risk appetite.

Design, build, and support SAP Analytics Cloud dashboards, planning models, and executive reporting. Integrate SAC with SAP and non‑SAP sources, develop KPIs and forecasting models, run testing and UAT, troubleshoot issues, and support production deployments and stakeholder workshops to deliver actionable analytics for FP&A and operational teams.

Lead architecture and delivery of a global analytics platform: build pipelines, semantic models, embedded analytics, and client-facing data products. Recruit and mentor analytics engineers, enforce governance, ensure observability and SLAs, and partner with executives and product teams to translate business needs into production-grade analytics solutions.

Lead the analytics team for the third-party agent business, driving business strategy, product analytics, and AI-powered insights while fostering cross-functional partnerships.

Lead and scale companywide analytics for a DTC marketing business: own marketing measurement, financial forecasting, retention/LTV modeling, data architecture, reporting, and the analytics team. Set analytics strategy, oversee data engineering roadmap, build dashboards, apply statistical and ML methods, and translate insights into executive-level decisions.

Lead revenue forecasting, planning, and executive reporting across new, renewal, and expansion revenue. Manage and grow a revenue insights team while owning pre-sales analytics, forecast methodology, capacity and quota planning, and performance narratives. Build pipeline and forecast reporting, track conversion/velocity metrics, surface risks early, and apply AI to improve forecasting, anomaly detection, and automated insights.

The Predictive Analytics Consultant designs and delivers analytics solutions for lending operations, focusing on predictive modeling, data transformation, and stakeholder communication.

Consult with financial institutions to analyze consumer credit and loan performance, evaluate underwriting and decision rules, develop data-backed lending recommendations, produce client reports/dashboards, and lead engagements using MeridianLink decisioning platforms and BI tools.

Build and operate the core BI platform: own ingestion, integration, modular dbt pipelines, and enterprise data models. Establish data quality, testing, governance, observability, and CI/CD. Monitor platform health, certify pipelines and data products, and mentor analytics engineers to enable trusted, self-service analytics and AI-augmented workflows.

Lead analytics and BI for Digital Product Operations: define product and adoption metrics, build dashboards, ensure data governance and quality, measure ProdOps effectiveness, coach PM/POs, diagnose adoption gaps, and drive interventions that improve product planning and delivery.

Lead demand forecasting and performance analytics for eCommerce: build forecasting models, run scenario and promotional analyses, produce executive reporting, drive cross-functional predictive initiatives, and deliver market and competitive insights to inform planning and resource allocation.

Lead analytics for the Credit Card portfolio, partnering with Product, Engineering, Credit Risk, Fraud, and Marketing to deliver data-driven strategy. Perform ad-hoc and cohort analyses, design A/B tests, manage BI reports, drive portfolio growth and risk insights, and build scalable data solutions with Data Engineering. Influence executives through clear recommendations and leverage AI tools to accelerate analytics and self-service.

Serve as embedded BI lead for a divisional sales book, delivering actionable insights from syndicated and commercial data, leading opportunity analysis, training field teams, supporting Power BI reporting, and translating complex data into executive presentations to drive sales performance and planning.

Lead end-to-end category insights for strategic account chains using syndicated, retailer POS, and internal data. Develop analyses, reporting, and recommendations to drive sales and profit, partner with sales and BI, support category reviews and business planning, and present insights to stakeholders.

Design, build, and maintain scalable Databricks-based data pipelines and ELT workflows; develop and document dbt models; define data modeling methodology; ensure data quality, reliability, and scalability; collaborate with clients and cross-functional teams; provide technical guidance and deliver improvements to clients' data infrastructure and analytics capabilities.

The Director of Product Analytics leads the product analytics strategy, develops a team of analysts, drives insights for product decisions, and oversees experimentation across products to enhance growth outcomes.

Lead product analytics efforts to define KPIs, build measurement frameworks, analyze customer behavior, and generate insights that influence product and engineering decisions. Partner with Product, Engineering, and Data teams to design event tracking, run experiments, quantify opportunity sizes, and communicate recommendations through clear narratives and visualizations to drive product adoption, retention, and business outcomes.

Lead BI developer who owns reporting infrastructure end-to-end: SQL-based data extraction from messy sources, LookML/BI model development, dashboard standardization, stakeholder partnership, and performance marketing optimization to drive actionable insights and business outcomes.

Design, build, and operationalize scalable analytics engineering solutions on Databricks and modern cloud platforms. Implement metrics-as-code and semantic layers, create automated pipelines, enable product measurement and experimentation, define cohorts and KPIs, improve data quality and governance, and lead engineering best practices and stakeholder delivery for data products.

Lead and scale customer analytics and intelligence to inform acquisition, engagement, retention, pricing, and commercial strategy. Build and manage an analytics organization, partner with Data Science and Data Engineering to deliver predictive models, real-time customer data layers, attribution and pricing analytics, and next-best-action frameworks. Translate complex insights into executive recommendations and operationalized data products to drive measurable business outcomes.

Produce and validate default reporting and analytics for mortgage servicing portfolios. Investigate data discrepancies, perform root-cause analysis, modify reports for ad-hoc needs, document processes, and collaborate with default management to ensure regulatory and investor-compliant reporting.

Lead commercial analytics to measure ROI, uncover growth opportunities, and deliver actionable insights. Build dashboards, perform SQL-based analyses, improve data quality, support forecasting, and implement automation/AI to streamline workflows. Partner cross-functionally with Sales, Marketing, Finance and Strategy to influence revenue and retention decisions.

Lead integration of technology into information systems, design data warehouse and BI capabilities, define data architecture and dictionaries, centralize disparate data, design dashboards, document system architecture, perform data quality and management, and provide solution engineering, pilots, and enablement for analytics and resource management.

Lead the design and implementation of analytics solutions, manage Adobe Analytics migrations, ensure data governance, and deliver cross-channel insights for customer journey optimization.

The CJA Business Analyst translates business analytics requirements into actionable tasks within Adobe Customer Journey Analytics, ensuring accurate reporting and effective migration from Adobe Analytics. Responsibilities include requirement gathering, validation, documentation, and collaboration with stakeholders.