Top Hybrid Data & Analytics Jobs in Indianapolis, IN

The Senior Business Intelligence Analyst will provide analytical support across various departments, focusing on billing and subscription analytics, to inform decision-making and improve business outcomes through data-driven insights.

Leads quantitative analysis of technology investments, implements cost-benefit frameworks, tracks performance, and advises executive leadership on investment priorities while fostering organizational data-driven culture.

As a Senior Associate in the Pricing team, you will design and integrate pricing applications, mentor junior associates, and ensure project quality while engaging with clients in complex revenue management scenarios.

As a Meteorologist, you will use forecasting tools to identify weather events impacting clients, communicate weather information, partner with analysts, and support customer webinars, all while working with a flexible schedule in a fast-paced environment.

The Senior Data Engineer will architect and implement data pipelines, manage their performance, and partner with stakeholders to ensure data accessibility and quality. Responsibilities include assessing data sourcing needs and providing visibility into pipeline status.

The Quantitative Researcher will analyze crypto markets, build trading strategies, and develop systems for performance analysis and risk management.

The Research Engineer will design and build evaluation systems to measure data quality for Firecrawl's web data extraction, creating metrics and benchmarks, and collaborating on model improvements.

The Data Engineer will develop ETL processes, maintain data pipelines, ensure data quality, collaborate with teams, and leverage cloud-based technologies.

The Quantitative Researcher will manage yield opportunities, design algorithms, perform risk analysis, and collaborate with engineers on DeFi strategies.

Design, build, and maintain dbt-based analytics-ready data models and curated data marts powering a PBM financial risk engine. Onboard and optimize claims, pricing, contract, and utilization data, implement data quality controls, support forecasting and risk metrics, and enable advanced analytics and ML operationalization for finance and underwriting stakeholders.