Top Senior Analytics Jobs in Baltimore, MD

Leads a client-facing healthcare analytics team that designs and maintains prior authorization decision automation programs. Consults PaaS clients, develops strategic roadmaps, translates requirements into technical blueprints, analyzes authorization and claims data, and builds KPI reports using visualization tools. Manages direct reports, improves analytics processes and AI tooling, partners with product and engineering teams, and ensures automation outcomes and client KPIs are achieved.

Designs and maintains scalable data infrastructure, ETL/ELT pipelines, canonical datasets, and AI context layers. The role improves data quality and alignment across sales and finance systems, investigates data inconsistencies, leads requirements through UAT and implementation, supports analytics self-service, and partners with cross-functional teams to deliver process improvements and reliable business data.

Build and maintain dbt data models, SQL transformations, ingestion pipelines, orchestration, and Tableau dashboards in support of HR and enterprise analytics. Own data quality, metric standardization, privacy controls, Row-Level Security, documentation, CI/CD, and troubleshooting from source systems through reporting. Partner with stakeholders to define requirements and KPIs, support workforce forecasting, optimize BigQuery performance, and pilot AI-assisted analytics using Google Gemini.

Own marketing measurement from initial engagement through closed-won revenue. Manage cross-channel reporting tied to Salesforce pipeline, tracking across GA4, advertising platforms, SEO, and AI search. Validate multi-touch attribution, analyze marketing experiments, model budget impact, and recommend investment priorities. Present performance insights to marketing and sales leadership across global regions.

Evaluate enterprise data architectures, governance frameworks, integration patterns, ownership models, and data quality practices. Design target-state architectures supporting analytics and AI, define governance operating models, assess data flows, develop quality controls, and create strategic roadmaps and executive recommendations. Collaborate with business and technology stakeholders on data modernization, cloud migration, AI enablement, and enterprise data management initiatives.

Build Deepgram’s governed decision layer above warehouse gold tables. Responsibilities include modeling cross-system entities, owning semantic and metrics definitions, creating agent-facing data tools and MCP surfaces, implementing data quality assertions and reconciliation checks, evaluating AI agent accuracy, and answering business questions while leaving reusable models behind. The role requires production-grade SQL and Python, semantic-layer ownership, strong data modeling judgment, AI-native workflows, clear writing, and comfort building infrastructure from scratch.

Leads enterprise data and analytics strategy, architecture, modernization, and delivery across cloud and on-premises environments. Oversees data platforms, engineering, integration, governance, quality, lineage, security, and compliance. Partners with executives to define roadmaps and investments, manages cross-functional teams and vendors, enables AI/ML capabilities, and mentors data professionals while driving scalable, trusted data solutions and measurable business outcomes.

Manages programmatic analytics and insights for client accounts, leading measurement frameworks, brand lift studies, incrementality testing, and A/B experiments. Develops media and campaign strategies, communicates performance insights to clients, and supports pitches and QBRs. Oversees, mentors, and develops analysts while partnering with Product, Engineering, Sales, and Customer Success teams to improve measurement tools, campaign optimization, and analytical capabilities.

Owns fraud performance analytics for depository products, including monitoring losses, approval rates, false positives, customer friction, and risk metrics. Builds data models, transformation pipelines, dashboards, scorecards, and monitoring frameworks. Conducts fraud deep dives and develops optimized rules, policies, thresholds, models, and decision strategies. Partners with Product, Engineering, Machine Learning, Data Engineering, Fraud Operations, and Risk teams to improve fraud detection and support product launches.

Leads analytics strategy and technical delivery for clients, specializing in Adobe Analytics and Customer Journey Analytics. Conducts measurement workshops, defines KPI and implementation strategies, oversees tagging and data quality, guides experimentation, and reviews dashboards and insights. Advises senior stakeholders, manages and mentors consultants, supports proposals and account growth, and contributes to Adobe Experience Platform initiatives involving Target, RT-CDP, and AJO.

Leads and transforms a sales performance analytics organization into a strategic, insight-driven business partner. Oversees analytics products, dashboards, forecasts, KPIs, governance, adoption, data quality, and responsible AI initiatives. Partners with senior sales, business, and technical leaders to rationalize reporting portfolios, prioritize high-value analytics, guide technical delivery, and translate complex data into actionable decisions. Coaches a multidisciplinary team and leads organizational change across a complex commercial environment.

Own analytics and reporting solutions for acquisitions, product launches, and other complex business events. Translate business changes into data models, system updates, processes, and reporting definitions. Coordinate Data Engineering, Analytics, Data Science, and Data Governance teams; lead cross-functional execution and establish a Business Intelligence Council. Partner across GTM, Finance, Product, IT, and other functions to reconcile metrics, clarify ownership, and maintain business visibility.

Lead analytics support for Fetch’s Food and Beverage vertical, serving as the primary analytics partner for Sales and client stakeholders. Own sub-vertical partnerships, manage analytic capacity, answer senior-level client questions, and guide campaign strategy. Use SQL to manipulate data, develop actionable insights, support QBR storytelling, and communicate recommendations to technical and non-technical audiences. Represent analytics cross-functionally and automate insights using AI-enabled tools.

Leads complex private banking data management and analytics initiatives, defining data strategies, quality standards, product attributes, and integrated client views. Partners with business, engineering, analytics, AI, and Wealth teams to translate needs into dashboards, KPIs, predictive models, personalized insights, and intelligent decision-making capabilities. Serves as a subject matter expert on private banking products while mentoring junior team members and enabling platform readiness.

Owns B2B and B2C funnel, enrollment, revenue, and marketing performance reporting. Builds executive and Board dashboards, analyzes CAC, LTV, retention, conversion, spend efficiency, and ROI, and reconciles marketing activity with financial results. Maintains KPI definitions and reporting governance while partnering with Marketing, Finance, FP&A, Sales Operations, and Data teams. Supports strategic planning, diligence requests, and actionable business recommendations through accurate, cross-functional analytics.

Lead insurance risk analytics engagements for property and casualty carriers. Responsibilities include product demonstrations, regulatory filing guidance, pilot and proof-of-concept design, loss ratio and model validation analysis, client project management, discovery sessions, and translating insights for actuarial, underwriting, and executive audiences. The role also develops AI-assisted workflows and provides customer feedback to product teams.

Lead and scale companywide analytics for a DTC marketing business: own marketing measurement, financial forecasting, retention/LTV modeling, data architecture, reporting, and the analytics team. Set analytics strategy, oversee data engineering roadmap, build dashboards, apply statistical and ML methods, and translate insights into executive-level decisions.

Analyzes healthcare claims, provider reimbursement, QPA, and dispute data to support No Surprises Act negotiations, arbitration, and OON liability management. Builds SQL-based reports, dashboards, data processes, and financial views; validates data quality; tracks dispute KPIs; integrates internal and external sources; and presents actionable recommendations to leadership and cross-functional stakeholders.

Analyzes paid media performance across the full funnel, connecting spend and platform metrics to applications, enrollment, student lifetime value, and ROAS. Builds attribution frameworks, Databricks data pipelines, Power BI dashboards, semantic models, and advanced DAX reporting. Supports marketing mix modeling, experimentation, web analytics data quality, forecasting, governance, and workflow automation. Translates complex analytics into strategic recommendations for executive and cross-functional stakeholders.

Build and operate trusted finance data products, pipelines, models, reconciliations, dashboards, and automation. Partner with Finance, Accounting, Data Engineering, Product, and Platform teams to resolve data issues, improve reporting, support financial close, establish data lake quality controls, and enable timely insights. Use SQL, Python, dbt, Spark, Airflow, and AI-assisted tools to deliver tested, traceable, production-ready solutions.

Lead and scale Runpod’s analytics and business intelligence function, managing analysts and BI practitioners while setting the analytics roadmap. Own core company metrics, consumption and marketplace analytics, self-service reporting, experimentation practices, and executive and board-level insights. Partner with Product, Finance, Engineering, Security, Supply, and Go-to-Market leaders to improve data quality, modeling, decision-making, and strategic outcomes.

Build and maintain product data models, ELT pipelines, semantic layers, and self-service analytics assets. Partner with Product Engineering and Data Governance to define canonical data, certify metrics, document taxonomies, monitor data quality, and support expansion and upsell analytics. Translate business requirements into governed data products, communicate insights to technical and non-technical stakeholders, and ensure data tooling complies with federal frameworks including FedRAMP and DoD IL4/5.

Leads operational analytics for the Take 5 Oil Change network, translating transactional and market data into insights that improve sales, profits, volume, and shop performance. Responsibilities include complex analysis, KPI reporting, dashboards, executive presentations, operational initiative measurement, stakeholder collaboration, data-quality improvement, and mentoring analysts. The role requires strong Excel, SQL, financial modeling, communication, and multi-shop operations experience.

Leads analytics, reporting, data modeling, automation, AI-agent development, and quality assurance for revenue cycle operations. Creates Power BI and Excel reports, analyzes complex healthcare and operational datasets, develops scalable warehouse models, and delivers actionable insights to leadership. Uses SQL, cloud data platforms, Git, Python, and AI-assisted tools to improve reporting efficiency, accuracy, and decision support.

Leads analytics for Pricing and Supply, managing a team of approximately eight analysts. Partners with cross-functional leaders to prioritize analytical work, build dashboards and decision frameworks, improve metric quality, and generate insights into pricing, supplier coverage, marketplace performance, conversion, margin, and customer behavior. Coaches analysts, establishes scalable analytics processes, and collaborates with data engineering teams to improve data models, tooling, and self-service capabilities.