Top Data & Analytics Jobs in Indianapolis, IN

Short-term, paid project to export and submit personal financial data from multiple apps. Participants must provide exports from specific financial categories, create two financial artifacts, redact PII on-device using a provided tool, and follow quality and timeline requirements until Final Approval.

Build and operate reliable ETL and ELT pipelines across lakehouse and transactional systems. Develop data models, enforce governance, integrate diverse data sources, and support analytics, APIs, and predictive tools. Monitor performance, data quality, lineage, cost, and uptime while collaborating with data science, AI, product, and innovation teams.

Lead enterprise adoption and toolchain integration for business analysis across federated teams. Design enablement curriculum, integrate standards and AI-enabled tooling (Azure DevOps, ServiceNow, Nexus, Power BI), build decision-oriented dashboards and leading indicators, drive adoption and governance, surface portfolio trends, and partner with stakeholders to improve delivery predictability and compliance.

Leads marketing experimentation, conversion optimization testing, incrementality analysis, marketing mix modeling, and statistical measurement programs. Designs rigorous experiments, manages SQL-based testing databases, validates data, develops executive reporting, and translates complex findings into investment and marketing recommendations. Partners with marketing, product, technology, analytics, and executive teams while potentially mentoring junior analysts.

Lead quantitative analytics for customer conversion, follow-up, retention, and recapture. Build KPIs, reporting, experimental measurement strategies, and complex T-SQL data solutions. Partner with Sales, Operations, Marketing, and Servicing leaders to identify opportunities and deliver actionable recommendations. Provide analytical leadership to other analysts while driving measurable revenue and business impact.

Develop and maintain quantitative models for forecasting, pricing optimization, and risk assessment. Analyze mortgage business metrics to identify revenue, profitability, and operational improvement opportunities. Build performance measurement frameworks, dashboards, automated reports, and SQL-based analytics workflows. Use Python for statistical analysis, automation, and machine learning workflows. Validate and monitor model performance, recalibrating models as needed, while communicating actionable recommendations to business leaders.

Design and operate Alpaca’s scalable data platform on GCP, including lakehouse infrastructure, Kubernetes-based deployments, streaming and CDC pipelines, batch ingestion, BI access, cataloging, monitoring, and governance. Build infrastructure as code with Terraform and Ansible, operate distributed query engines and Apache Iceberg, maintain reliability practices, and collaborate with DevOps and analytics teams to support rapidly evolving data requirements.

Develops scalable business intelligence and analytics solutions for Microsoft’s cloud data center delivery lifecycle. Builds data assets, dashboards, models, and automated workflows; improves data quality and reporting; translates complex business questions into analytical requirements; identifies process improvements; and delivers actionable insights to technical and executive stakeholders through cross-functional partnership.

Build and maintain large-scale data processing pipelines using Apache Spark (PySpark/Scala) and Python. Design ETL workflows, implement distributed data processing, use version control (Git), and work with cloud platforms (GCP/AWS/Azure).

We are seeking an experienced data analyst to maximize our service offerings through data mining, generation, and visualization, while producing goal-oriented reports.

Performs data quality checks, validates data after system and process changes, investigates discrepancies, and identifies root causes. Maintains quality rules and documentation, tracks issues, prepares reports, monitors trends, and coordinates resolutions with Data, Engineering, Product, and Operations teams. Supports testing of data workflows and product features while recommending improvements to data processes and controls.

Collects, cleans, and organizes structured data; prepares recurring reports and dashboards; identifies trends and inconsistencies; performs data quality checks; tracks business and product metrics; supports senior analysts with research and ad hoc analysis; documents findings; and collaborates with Data, Product, Engineering, and Operations teams.

Build and maintain dashboards, reports, and recurring business intelligence solutions. Analyze business and product data, define KPIs, validate reporting accuracy, investigate discrepancies, and present actionable insights. Translate stakeholder needs into analytical requirements, collaborate with Data, Product, Engineering, and Operations teams, document data assets, and improve or automate reporting processes.

Develop statistical, machine learning, and deep learning models to measure the impact of pharmaceutical HCP, DTC, and Medical Affairs campaigns. Partner with internal and external clients, provide analytical insights and methodological guidance, consult with sales and market research teams, and coach an offshore analytics team. The role requires applying causal inference, healthcare and pharmaceutical data expertise, and clear communication of findings to clients and executives.

Analyzes platform usage, client growth, query performance, infrastructure capacity, and cloud/AI costs. Builds scaling scenarios, monitors AWS and GCP utilization, identifies anomalies and waste, owns product analytics reporting, and partners with Engineering and Product on database scaling decisions. The role also documents optimization results, capacity thresholds, vendor utilization, and model assumptions while translating technical findings for business stakeholders.