Top Remote Analytics Manager Jobs

Leads strategy, roadmap, development, and adoption of analytics and AI products for Ford Integrated Services. Owns reporting platforms, dashboards, governance, metrics, support models, and generative AI initiatives. Partners with senior stakeholders and cross-functional teams including engineering, design, data science, and analytics to deliver actionable insights, improve subscriptions performance, and establish trusted business intelligence solutions.

Lead HEDIS, Medicare Stars, and ACO quality measurement and reporting; manage data integration, vendor and audit coordination, performance analysis, and quality improvement initiatives. Oversee a cross-functional analytics team, ensure regulatory compliance and timely submissions, and support strategic planning and stakeholder collaboration to optimize quality scores and financial outcomes.

Early-career Product Manager in analytics/strategy focusing on behavioral data analysis, A/B testing, funnel diagnostics, and recommendation ranking optimization. Produce strategy docs and PRDs, collaborate with algorithm teams, develop labels/taxonomies, and deliver actionable insights from experiments and data extraction.

Leads customer-facing healthcare analytics for medical claims, economics, health plan performance, and cost mitigation. Advises account teams and clients by translating complex data into strategic recommendations, oversees analytics priorities and resources, collaborates with clinical consultants, and supports retention and growth objectives. Requires strong healthcare industry knowledge, medical economics expertise, relationship management, communication, project management, and advanced analytical skills.

Own the strategy, governance, architecture, modeling, and reporting foundation for People Experience data. Build governed metrics, semantic and consolidated data layers, dashboards, data catalogs, quality monitoring, and operating processes from the ground up. Manage intake, prioritization, access, privacy, enablement, and self-service adoption while partnering with stakeholders on analytics and future AI capabilities. The role combines strategic program leadership with hands-on SQL, data modeling, reporting, and team mentoring.

Own the end-to-end reporting and analytics product roadmap, from customer discovery and requirements gathering through delivery, release readiness, and adoption. Design scalable self-service reporting systems, translate needs into product specifications and user stories, prioritize investments with stakeholders, and collaborate with Engineering and Data Science. Monitor usage to improve report usability and reduce reliance on ad hoc requests.

Owns the end-to-end architecture, development, infrastructure, data pipelines, and Power BI reporting platform supporting data governance, informatics, analytics, auditing, and data quality. Leads and mentors a data engineering team, defines schemas and engineering standards, ensures security and HIPAA compliance, oversees testing and Agile delivery, manages stakeholder requirements, and remains hands-on with backend technologies, data models, Power BI, and DAX.

Lead pricing strategy and analytics: develop pricing, packaging and monetization recommendations; build forward-looking revenue/volume models; maintain pricing algorithms and reporting; collaborate with Sales, Finance, Marketing and Data teams to implement pricing actions and standardize quantitative outputs.

The Manager of Advanced Analytics will lead the design and implementation of data solutions, mentor team members, and collaborate with stakeholders to drive analytics strategy and improvements in patient outcomes.

Lead analytics for Wealth Solutions: analyze client segmentation, revenue, and operational data; build models for capacity and workforce planning; produce insights and recommendations for senior leadership; partner with BI and Finance to improve advisor productivity, client experience, retention, and revenue growth; support strategic projects and translate complex data into clear presentations.

The Senior Manager of Risk Analytics will lead credit risk strategies, manage portfolio performance, optimize decisioning frameworks, and drive business growth through analytics and predictive modeling.

Lead revenue cycle analytics for a new service line: design and maintain Snowflake SQL data models, build end-to-end Power BI reports, perform root-cause analyses, govern KPI definitions, QA datasets, and advise directors, executives, and clients to drive data-driven revenue cycle decisions.

Serve as the ISSO/ISSM for a DoD application: integrate cybersecurity across the lifecycle, implement and monitor RMF controls, identify and remediate vulnerabilities using Fortify, and develop POA&Ms to achieve and maintain authorization.

Lead a marketing analytics team to deliver acquisition, engagement, retention, and reactivation measurement. Own SQL-based analyses, experiments, audience strategies, dashboards, and incrementality methods. Translate business questions into analytical plans, partner cross-functionally, mentor analysts, and connect marketing activity to downstream outcomes like retention, revenue, and lifetime value.

Lead a team delivering product and business analytics for Fetch's commerce and shoppable experiences. Own prioritization, experimentation, measurement, KPI dashboards, and stakeholder-facing insights to inform product, marketing, and commercial decisions. Manage and develop analysts while partnering cross-functionally to ensure data quality, repeatable analyses, and actionable recommendations.

Lead Workday reporting operations and governance, manage a small team, build and validate advanced Workday reports and dashboards, maintain documentation and standards, partner with HR and stakeholders to deliver accurate HR reporting and improve data quality.

Own strategy, roadmap, and execution for client-facing analytics and AI insights. Deliver dashboards, reports, and conversational NLQ analytics. Partner with data engineering, data science, and platform teams to shape semantic models and LLM-backed analytics. Drive adoption with Sales, Customer Success, and Implementation teams and use AI tools to accelerate product work.

Lead end-to-end funnel analytics and optimization for SMB lending, identifying friction and bottlenecks, designing measurement frameworks, running experiments (A/B testing), and partnering with Risk, Operations, Product, Engineering, and AI teams to deploy automation and AI solutions that improve conversion, cycle time, and customer outcomes while managing risk.

The role involves designing and implementing integration solutions using iPaaS technologies, managing development processes, and mentoring team members while ensuring client satisfaction.

Lead product vision and roadmap for data and analytics products (ML, generative AI, data pipelines, BI). Translate business needs into developer-ready features, maintain backlog, collaborate with engineering and stakeholders, track KPIs, and drive adoption and continuous improvement.

Lead revenue operations and analytics to ensure accurate reporting, scalable systems, and cross-functional execution. Build executive dashboards, drive revenue planning and forecasting, optimize CRM and reporting tools, manage sales compensation and GTM processes, and lead initiatives to improve conversion, reduce timelines, and support executive decision-making.

Lead and own the population health analytics pipeline: intake and reconciliation of claims, eligibility, and MAO-004 data; identify and reconcile care gaps and closures; deliver practice-level performance analysis and billing reconciliations; build funnel instrumentation; document, standardize, and automate pipelines with Product and Engineering. Ensure billing-grade accuracy and support program measurement aligned to CMS reconciliation windows.

Lead and mentor an analytics team to design and implement data-driven solutions, align analytics with strategy, manage Agile workflows, build stakeholder relationships, and monitor KPIs to improve healthcare delivery and outcomes.

Own audience analytics across website, email, and events to define KPIs (LTV, time spent, repeat visitation), reconcile data across CRM/ESP/revenue systems, build segments and re-engagement strategies, drive personalization and retention, report trends, and partner cross-functionally while using AI/agentic tools to scale insights and measurement.

Lead design and delivery of analytics, dashboards, and data models for Compensation and Benefits. Partner with Total Rewards, HR, Finance, and Technology to provide actionable insights, drive pay equity and regulatory reporting, and implement automation, data governance, and predictive analytics to improve program effectiveness and decision-making.