Top Remote Data & Analytics Jobs in Indianapolis, IN

The Senior Director will establish and lead the Real-World Data & Analytics group, oversee RWD strategy, engage in complex analytics projects, and build a high-performing team in the oncology domain.

The Data Insight Analyst develops reports and analyses using SQL and Excel, provides consultative insights into data trends, manages client requests, and configures mapping tools for data reporting and quality assurance.

Senior individual contributor who builds centralized analytics (Power BI), delivers insights for underwriting and distribution, standardizes surety marketing content, drives operational efficiency and automation, and leads cross-functional strategic initiatives to improve decision-making and execution.

The Lead Data Engineer will optimize data pipelines, collaborate with teams, and maintain the analytics platform in a changing environment to deliver solutions that meet business needs.

Lead acquisition, cleaning, validation, storage and protection of datasets to support reporting and analysis. Design and execute data architectures, policies and ETL pipelines (SSIS, ADF) using cloud platforms (Azure Synapse, Snowflake, Databricks). Deliver dimensional models, visualizations, and lifecycle governance to make complex data accessible and drive business insights.

Analyze IVR caller behavior using SQL and Excel, build Tableau reports to visualize trends, collaborate with stakeholders to improve IVR user flows, and provide data-driven recommendations to enhance caller experience.

Analyze conversational call flows and large datasets to optimize IVR and generative AI systems. Perform call testing, annotation, dashboard monitoring, and deliver data-driven insights and presentations to improve self-service, reduce agent handling, and enhance customer experience.

Analyze complex pharmaceutical transaction data, build forecasts and custom models, create dashboards and reports, identify trends and actionable insights, implement data quality/observability and process improvements, communicate technical specifications to stakeholders, mentor junior team members, and support cross-functional product and client initiatives while ensuring regulatory compliance (including HIPAA).

Analyze complex pharmaceutical transaction data to build forecasts, models, dashboards, and actionable insights. Partner with stakeholders to design data models, automate processes, ensure data quality and compliance (HIPAA), debug issues, document requirements, mentor juniors, and translate technical specifications for business users.

Lead media analytics for Marriott Media Network by designing measurement methodologies, running A/B tests and MMM, analyzing audience and campaign performance, translating data into executive-ready insights, and partnering cross-functionally to optimize monetization and media strategy.

Senior finance-focused data analyst responsible for owning finance, accounting, and revenue data pipelines; building forecasts, scalable SQL transformations, repeatable dashboards, and analytics; delivering accurate reports and insights to stakeholders including C-suite; ensuring QA, documentation, and cross-functional collaboration to drive actionable recommendations.

Perform advanced quantitative analyses, build and maintain dashboards and automated reports, collaborate across teams to drive data‑driven decisions, lead process improvements, and mentor junior analysts.

Lead design, build, and operate real-time, Flink-based streaming data platforms. Develop low-latency, stateful pipelines, enforce event schemas/contracts, ensure fault tolerance and observability, mentor engineers, and partner with architecture and compliance teams to deliver resilient streaming solutions for banking use cases.

Design, build, and maintain scalable, secure data pipelines and platforms to acquire, transform, and store large financial datasets. Enable AI/GenAI-ready data foundations for model training, inference, retrieval, and RAG workflows. Collaborate with cross-functional teams, ensure data quality, governance, observability, and compliance, and support production deployments and troubleshooting.

Lead graph data engineering to design, implement, and scale Neo4j-based graph platforms. Build graph models, ingestion pipelines (batch and streaming), integrate graphs with analytics/ML, establish governance, and enable graph-driven business use cases like fraud detection and Customer 360.