Top Data & Analytics Jobs in Baltimore, MD

The Principal Statistical Programmer manages statistical programming for clinical trial data, ensures quality and compliance for CDISC standards, and mentors junior staff.

The Senior Pricing and Paywalls Product Analyst will automate analytical data collection, analyze product metrics, organize A/B tests, and support the generation of product hypotheses to identify growth opportunities.

The Fraud Analyst monitors transactions for suspicious activity, uses fraud detection tools, documents findings, communicates with clients, and supports the Risk & Compliance team.

Lead global partner analytics and planning for partner GTM motions. Build dashboards, business models, AI-enabled workflows, and executive reports to support partner planning, incentives, coverage, performance management, and cross-functional decision-making across hyperscalers, ISVs, marketplaces, and reseller channels.

Lead data-focused business analysis: elicit and document requirements, model data and processes (As-Is/To-Be), design data flows, support integrations, migrations, EDW/reporting decisions, mentor team members, and drive data governance and cataloguing across enterprise systems.

General application to Cardamom's talent pipeline for roles across Epic analytics, data & analytics, project/product management, and internal functions. Candidates can submit for Epic analyst, data engineering, data science, interoperability, BI, software development, and entry-level roles (Madison local). Talent team reviews submissions and contacts matches for current or upcoming openings.

Lead Southern California risk, actuarial, and analytics strategy for employee benefits. Serve as market-facing advisor, drive client retention and growth, oversee advanced modeling (funding, stop-loss, forecasting), lead analytics team, scale delivery, and partner with national centers of excellence to align tools and execution.

Lead enterprise analytics initiatives across Sales, Marketing, and Operations. Build predictive and statistical models, create KPI dashboards, translate data into executive-ready insights, mentor junior analysts, and partner with stakeholders and data engineering to deliver actionable recommendations that improve acquisition, retention, and channel performance.

Design, build, and scale reliable batch and real-time data pipelines and warehouses. Partner with engineering, data science, and business teams to define data models, improve observability, optimize storage and querying, and evangelize data engineering best practices across the company.

Lead architecture and implementation of scalable data systems and pipelines from ingestion to delivery. Own ambiguous, high-impact integrations, improve data quality and reliability, adopt AI-augmented engineering, mentor engineers, and collaborate with Product, ML, and customer teams to ship production solutions.