Top Senior Analytics Jobs in Indianapolis, IN

Design, build, and maintain scalable data models and BI semantic layers. Partner with analysts and business teams to translate requirements, enforce modeling/testing standards, resolve data quality issues, mentor colleagues, and evaluate new data tooling to support dashboards, self-serve analytics, and AI solutions.

Design, build, and maintain enterprise risk analytics and automated reporting (SAS/Python/Tableau). Translate senior stakeholder needs into scalable dashboards, committee reports, and repeatable pipelines, enabling proactive risk insights and automation.

The Business Strategist will align client strategies with data analysis solutions, managing projects and analytics to provide insights and recommendations for business growth.

Lead design and delivery of Workday reporting and analytics for AMS clients: build advanced/matrix/trending/composite reports, dashboards, Discovery Boards, Worksheets, and complex calculated fields; gather requirements, optimize reports, mentor junior consultants, and provide Workday best-practice guidance.

Owner of the analytics foundation: design and maintain BigQuery/dbt models, pipelines, and Looker Studio reporting; build AI workflows and web apps on GCP; integrate marketing, e-commerce, and fulfillment data; ensure GCP ops, security, and reliability; use AI-assisted tools daily and collaborate with business and client stakeholders.

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.

Lead growth of the Customer Analytics practice for Communications, Media & Technology clients. Define strategies and thought leadership, communicate analytics value, and lead large-scale client engagements. Oversee customer analytics delivery, CRM modeling, reporting, and predictive analytics initiatives.

The Senior Analytics Engineer will design and implement scalable data solutions for Finance Analytics, reconcile data accuracy, and collaborate across teams to enhance financial datasets and reporting workflows.

Lead end-to-end business analysis for data and technology projects: elicit requirements, create BRDs/functional specs/user stories, map processes, profile source data with SQL, build source-to-target mappings and documentation, support agile delivery and UAT, coordinate stakeholders, and present actionable recommendations to clients.

Lead design and implementation of tracking with GTM, analyze user behavior in GA4, build BigQuery queries and dashboards, define KPIs with cross-functional teams, troubleshoot tagging/data issues, and perform deep-dive conversion and journey analyses to optimize web and mobile performance.

Own and build scalable analytics models, metric definitions, and dashboards (customer-facing and internal). Partner with engineering to design data flows and instrumentation (BigQuery, S3, PostHog). Translate stakeholder needs into analytics plans, triage requests, and surface insights via Looker/Observable. Set analytics stack direction and ensure data quality.

Lead complex analyses of large healthcare datasets to evaluate growth opportunities, measure test-and-learn results, build dashboards and automated reports, enable self-service analytics, and present actionable insights and recommendations to stakeholders to drive pharmacy prescriptions and immunizations growth.

Execute underwriting and case-valuation analytics: write and optimize SQL, build dashboards, maintain valuation models, forecast case outcomes, monitor portfolio performance, and translate insights for operational and marketing stakeholders.

Lead embedded BizOps analytics for a core business area (growth, product, AI, or partnerships). Define problems, build metrics, reports, experiments, and analyses, and drive data-informed recommendations end-to-end to influence leadership and deliver measurable business outcomes.

Own the end-to-end analytics function embedded in a core business area (growth, product, AI, partnerships). Define problems and metrics, build reports, run analyses and experiments, surface insights, make recommendations, and drive outcomes with cross-functional teams.

As an Analytics Engineer, transform raw data into metrics, manage data pipelines, ensure data integrity, and collaborate with teams for analytics solutions.

Lead a centralized Decisioning Analytics team to measure and optimize Pega-powered Next-Best-Action decisioning. Own measurement frameworks, ADM performance, transparency, governance, cross-functional partnerships, NBA analysis, roadmap, and team development to drive measurable customer and financial outcomes.

The Analytics Lead will guide data-driven decision-making, develop measurement frameworks, forecast revenue, and mentor an analytics team, ensuring effective communication of insights.

Lead Oracle Cloud reporting initiatives, ensuring data accuracy and performance while mentoring junior analysts and collaborating with stakeholders.

Lead analytical efforts in Real World Data research, develop specifications and methodologies, manage projects, and communicate findings to stakeholders.

The Senior Data Analytics Engineer will develop data pipelines, support data-driven decision-making, collaborate with stakeholders, and improve data quality and processes.

The Senior Data Scientist will build frameworks for data-driven decision making, develop predictive models, ensure data quality, and enhance customer experiences through analytics and operational insights.

Lead architecture and execution of Grafana's marketing data stack and analytics practice. Build forecasting, predictive, and causal models, design BigQuery schemas, deploy agentic AI and automated pipelines, partner with GTM leadership, and deliver executive-grade insights to drive demand generation and ROI.

The Senior Analytics Engineer will design and build scalable data pipelines using dbt and Snowflake, providing technical guidance, conducting audits, and mentoring junior engineers while leveraging AI tools to enhance productivity.

Lead analytics and data science initiatives to drive measurable business outcomes across various functions, including Underwriting and Claims. Oversee the full analytics lifecycle, foster stakeholder engagement, and mentor junior team members.