Top Data & Analytics Jobs

Analyzes payments and banking data to identify trends, improve products, and enhance operational efficiency. Builds dashboards, conducts deep-dive and experimental analyses, monitors customer behavior, and delivers actionable insights to stakeholders. Partners with product managers, engineers, and leadership to define success metrics, ensure data quality, support fraud response, and improve analytics processes.

Lead supply chain analytics and AI initiatives focused on MRP accuracy, inventory optimization, production scheduling, and process improvement. Develop statistical, machine learning, generative AI, and reporting solutions; manage supply chain metrics and data governance; optimize SAP MRP parameters; support SIOP planning; and partner with procurement, manufacturing, engineering, and IT teams. Mentor analysts and data scientists while driving automation, analytics strategy, and measurable operational improvements.

Own actuarial models and client-facing reporting measuring cost savings, outcomes, and performance of healthcare prior authorization programs. Analyze authorization and claims data, conduct impact evaluations, reconcile projected and realized results, investigate trends, and present executive-level insights to customers and leadership. Partner with clinical, customer success, data, and actuarial teams while maintaining reproducible, auditable methodology and documentation.

Lead data engineering initiatives supporting analytics, machine learning, and business intelligence teams. Design complex data warehouse and data lake models, manage large-scale SQL and Python ETL/ELT pipelines, maintain data quality and lifecycle standards, and translate strategic priorities into actionable projects. Provide technical leadership, mentorship, architectural guidance, project planning, and cross-functional collaboration with product, infrastructure, and architecture teams.

Leads the commercial analytics function, developing advanced analytics frameworks, performance metrics, dashboards, forecasts, and strategic insights. Partners with senior leadership and cross-functional teams to optimize sales performance, resource allocation, commercial strategy, and operational efficiency. Oversees data quality, competitive analysis, sales compensation planning, analytical tools, and direct-report performance while promoting data-driven decision-making across the organization.

Administer and enhance Edmunds’ Databricks data platform and AWS infrastructure. Build and maintain ETL pipelines, infrastructure-as-code tooling using Terraform or CDK, and operational dashboards, alerts, and reports. Collaborate with business, engineering, analytics, security, and infrastructure teams to support data platform users and AI solutions. Evaluate new technologies, troubleshoot platform issues, and improve operational, cost, and security visibility.

Business Analytics Interns will transform and model datasets, analyze customer and business data, build dashboards, support ad hoc investigations, and translate stakeholder questions into actionable insights. The role also involves communicating findings to technical and non-technical audiences and exploring AI tools to improve analytical workflows and self-service analytics. The internship runs approximately 30 hours per week from October 6 through December 17, 2026.

Support GTM compensation lifecycle, quota/target setting, and performance analytics. Reconcile commission data across systems, build reporting, model scenarios, and deliver decision-ready insights to RevOps and GTM leaders.

Build scalable, secure data pipelines, models, platforms, and governance systems that enable AI applications to access trusted enterprise data. Partner with analytics, marketing, and product teams to translate requirements into technical solutions, independently deliver projects through production, and support sensitive-data security and access controls. Preferred experience includes LLM architectures, cloud data platforms, infrastructure as code, regulated environments, and technical leadership.

Lead analytics engineering by developing scalable data models, defining analytics requirements, and delivering data products for company stakeholders. Establish standards for data structure, quality, documentation, testing, version control, and development practices. Partner with analysts, engineers, product managers, and other teams to improve data accessibility and decision-making. Requires expertise in SQL, Snowflake, dbt, BI tools, and analytics engineering practices, plus fintech experience.