Top Senior Analytics Jobs in Baltimore, MD

Build and maintain SQL-based marketing analytics infrastructure, data models, dashboards, and reporting. Analyze marketing channels, affiliates, conversion funnels, cohorts, revenue, profitability, and partner performance. Translate complex findings into actionable recommendations for budget allocation and optimization. Ensure data quality, governance, documentation, and metric consistency while partnering cross-functionally with Marketing, Sales, Finance, Operations, Product, and Technology. The role is a hands-on individual contributor with potential responsibility for mentoring or managing one analyst.

Own regulatory analytics and reporting by building audit-ready datasets, dashboards, data models, pipelines, governance controls, and compliance automations. Analyze complex financial and compliance data, support audits and risk assessments, monitor data quality, and translate regulatory requirements into reliable reporting solutions using Python, SQL, dbt, and Airflow. Partner with engineering, analysts, compliance teams, and leadership to deliver actionable insights and improve regulatory processes.

Lead a small analytics team (staff data scientist + two analysts) to deliver curriculum, product, and program insights. Split time between people management (60-70%) and hands-on analysis (30-40%), advance experimentation and measurement, build AI/LLM-driven agentic workflows, manage sprints and cross-functional stakeholder relationships, and drive analytics that inform curriculum, product, and intervention strategies.

Designs, builds, and maintains enterprise data pipelines, ETL processes, integrations, data infrastructure, and complex data models. The role supports analytics partners, develops scalable data warehouse solutions, tunes SQL and databases, troubleshoots production issues, and collaborates with architects, analysts, developers, and stakeholders. Responsibilities include end-to-end project delivery, data modeling, big data engineering, production support, agile planning, and mentoring team members.

Leads scalable data model and pipeline design, dbt development, testing, CI/CD, and analytics engineering implementations. Partners with analysts, engineers, and stakeholders to translate business needs into reliable models and semantic layers. Advises on data architecture, governance, quality, performance, and long-term scalability while mentoring peers and contributing to shared tooling, standards, and frameworks.

Lead a GTM Analytics team supporting Marketing, Sales, RevOps, and Customer Operations. Manage embedded analysts, establish trusted reporting and QA processes, review SQL and dashboards, guide funnel, campaign, sales, support, forecasting, segmentation, attribution, and experimentation analysis, and deliver executive recommendations. Partner with GTM leaders and data engineers, coach analysts, and develop self-service analytics, automation, governed dashboards, metric documentation, and AI-assisted workflows.

Leads a team of five experienced analysts and data scientists while personally owning strategic analytics across ecommerce, health, supply chain, inventory, fulfillment, and merchandising. Partners with executives, establishes KPI and reporting standards, prioritizes the analytics roadmap, and delivers actionable business insights. The role also advances AI-native, self-service analytics capabilities, strengthens data governance and quality, and builds a high-performing analytics culture.

Build and maintain invoicing, reimbursement, revenue recognition, claims, and financial reporting models using SQL and dbt. Reconcile merchant, operational, warehouse, and accounting data; investigate variances; validate expenses; and establish automated financial controls. The role also triages data issues, investigates production APIs, supports audits, partners on merchant configuration, and drives upstream fixes through root-cause analysis and automation.

Leads enterprise analytics strategy, measurement frameworks, KPI development, dashboards, reporting, and insights for B2B commerce, marketing, and customer experience clients. Oversees analytics implementations across web, commerce, CRM, CDP, BI, and data platforms; mentors analysts and consultants; manages data quality and governance; leads executive client discussions, workshops, proposals, and business growth opportunities.

Own the analytics data layer by translating stakeholder needs into certified dimensional models, governed metrics, semantic layers, dashboards, and reports. Build with dbt, SQL, Databricks, Power BI, and Airflow while ensuring data quality, observability, reconciliation, documentation, and dependable orchestration. Partner closely with finance, operations, and client-facing teams, automate recurring workflows, and use AI-assisted engineering practices in a fully remote environment.

Leads and develops a data engineering team supporting People Analytics and AI-assisted workforce analytics. Designs scalable data models, pipelines, semantic layers, testing frameworks, and governance practices. Remains hands-on with production code, reviews, and technical problem-solving while partnering with People Analytics, business, legal, and compliance stakeholders. Establishes engineering standards across Python, SQL, dbt, Airflow, Snowflake, CI/CD, data quality, observability, privacy, and security.

Leads the Sales Analytics and Reporting function and manages Sales Analysts. Oversees dashboards, scorecards, KPI tracking, profitability analysis, business insights, executive reporting, and sales technology platforms. Partners with Sales, Finance, Product, Technology, and other stakeholders to improve performance, profitability, planning, and decision-making. Develops team capability, reporting processes, platform adoption, and analytical effectiveness while translating complex data into actionable recommendations.

Manage human capital analytics and workforce metrics, including hiring-process analysis, time-in-stage, time-to-hire, yield rates, benchmarking, trend analysis, and performance measurement. Develop dashboards, visualizations, executive briefings, analytical presentations, and reports using business intelligence tools. Communicate complex findings and actionable recommendations to senior leadership while supporting federal or large organizational clients.

Lead identification and quantification of issuance leakage across acquisition, application, approval, and funding funnels. Analyze digital customer journeys and conversion gaps, run root-cause diagnostics, design experiments, build executive dashboards, and translate findings into prioritized, quantified business recommendations partnering with Product, Marketing, Credit Risk, Operations, and Engineering.

Lead complex customer analytics engagements, translating industrial business needs into scalable analytics architectures and solutions. Advise customers, drive product adoption, identify high-value use cases, mentor Analytics Engineers, resolve technical escalations, and influence product roadmaps. Apply expertise in industrial process data and sectors such as power, pharmaceuticals, and semiconductors. Collaborate with customers, partners, product teams, and account teams to deliver measurable business 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 independent validation and governance of credit and fraud models, build automated Python monitoring for model drift and performance, drive remediation with model developers, and liaise with audit and regulators to support Affirm Bank's model risk management.

Lead revenue-cycle performance analyses, diagnose root causes, quantify value (ROI/collections lift), and translate findings into pragmatic, stakeholder-ready recommendations. Partner cross-functionally to scope analyses, validate data, and drive strategic workstreams that inform product roadmap and client outcomes.

Serve as a strategic analytics advisor to clients, designing and auditing Adobe Analytics and Customer Journey Analytics implementations. Lead measurement workshops, requirements gathering, documentation, report suite and CJA configuration, identity resolution, dashboard development, and data storytelling. Translate ambiguous business needs into actionable analytics strategies, present findings to executives, deliver training, and guide technical and non-technical stakeholders. Promote information security and data privacy practices, including GDPR and CCPA compliance.

Design and own an event-driven data architecture that moves healthcare claims data through AWS and Snowflake into fraud, waste, and abuse alerts. Establish architecture standards, approve material changes, build complex pipeline components, and ensure scalability, reliability, and compliance with PII/PHI constraints. Collaborate with data science, compliance, technical, and investigative teams while supporting government review timelines. This is a hands-on principal role requiring strong Python, SQL, AWS, Snowflake, and production streaming pipeline experience.

Lead and build a product analytics function: define KPI framework, instrumentation, and self-serve analytics using Pendo and BI tools. Partner cross-functionally to measure product performance, surface insights, influence roadmap and embed AI-powered analytics into product lifecycle.

Architects and scales enterprise data models, dimensional models, dbt transformation pipelines, semantic layers, and BI datasets. The role focuses on data quality, testing, observability, governance, metric standardization, documentation, performance optimization, and secure access controls. It partners with executives and cross-functional teams, leads analytics engineering initiatives, troubleshoots complex data issues, owns domain models, and mentors engineers while advancing the company’s analytics platform strategy.

Build and maintain governed Silver/Gold data models and semantic assets on Databricks. Translate stakeholder KPIs into testable, reusable transformations, apply enterprise modeling standards, enable domain self-service, ensure data sensitivity and governance, and review domain-contributed models for production readiness.

Build Sailor Health’s foundational data platform from scratch. Responsibilities include developing Snowflake and dbt pipelines integrating EHR, CRM, and communications data; creating data-powered web applications; automating clinical and billing workflows with Python; analyzing therapy transcripts and patient data using AI and machine learning; tracking clinical outcomes; and designing scalable data architectures in collaboration with clinicians, engineers, founders, and other teams.

Analyze sales, marketing, and customer success performance, including pipeline, funnel conversion, campaigns, retention, and revenue drivers. Build and maintain dbt models and marts using Salesforce and modern data-stack tools, while owning data quality and documentation. Contribute to Lighthouse, a BI-as-code platform, and develop AI-assisted analytics workflows. Partner with stakeholders to frame ambiguous questions, deliver recommendations, and communicate progress in two-week sprints.