Top Remote Analytics Manager Jobs

Own client relationships and analytics strategy across digital measurement and GEO initiatives. Architect, audit, and QA GA4 and Adobe Analytics implementations; develop measurement frameworks, dashboards, experimentation plans, and causal analyses. Present insights to executive stakeholders, manage analytics workstreams, mentor teammates, and build AI-assisted workflows, automations, and scalable systems. The role combines traditional analytics with measurement of AI-powered search visibility and customer behavior.

Leads marketing measurement, forecasting, attribution, media mix modeling, and LTV/CAC analysis across D2C channels. Builds analytical infrastructure, evaluates channel performance, supports budget allocation, and conducts cohort and retention analysis. Partners with executives, marketing, finance, product, and data engineering to translate complex findings into actionable recommendations. The role also establishes reporting for new channels, supports scenario planning, and communicates insights that guide growth and investment decisions.

Leads revenue planning and analytics, including forecasting, ASP and reimbursement analysis, pricing governance, contract economics, and commercial performance reporting. Manages revenue risks, develops executive insights, establishes financial models and controls, and partners cross-functionally with FP&A, accounting, market access, RCM, commercial, and operations teams. Directly manages and develops a senior analyst while ensuring forecast accuracy, data quality, and disciplined commercial decision-making.

Own marketing performance measurement and causal testing across growth channels. Design holdout and incrementality experiments, standardize conversion definitions and campaign taxonomy, build a trusted reporting layer using BI tools, and translate statistical findings into executive recommendations. Partner closely with embedded data science, marketing, client success, and product teams to guide channel investment and optimization.

Leads a team of data scientists and analysts delivering advanced analytics, machine learning, forecasting, AI-enabled decision support, and self-service solutions. Owns portfolio prioritization, analytical quality, stakeholder alignment, governance, adoption, and business impact measurement. Coaches technical talent, translates business problems into scalable analytical products, partners with IT and compliance teams, and maintains hands-on technical involvement in priority work.

Leads supply chain analytics product management, business intelligence, and decision intelligence. Manages decision scientists, product owners, and BI developers; defines analytics roadmaps, prioritizes backlogs, establishes KPIs, oversees delivery and adoption, and develops decision tools. Partners cross-functionally with data engineering, data science, automation, IT, and supply chain teams while coaching staff, improving governance, and promoting AI-enabled productivity.

Lead cross-functional supply chain analytics and AI initiatives, including forecasting, supplier-risk modeling, should-cost analysis, dashboards, optimization scenarios, and LLM-powered workflow tools. Translate procurement, planning, finance, and capital-project needs into actionable analytical solutions, partner with data engineering on governed datasets and deployment, and manage implementations across stakeholders. The role requires strong supply chain knowledge, applied AI experience, BI proficiency, predictive modeling expertise, and willingness to travel to supplier and operational sites.

Leads the data, analytics, and AI team; consolidates the company data warehouse; governs cross-system reporting and metric definitions; oversees pipelines, data quality, security, and upstream integrations; prioritizes the team backlog; manages and grows a distributed team; and delivers automation and AI tools. The role requires strong data engineering, analytics, BI, governance, business communication, and platform decision-making skills. Travel occurs approximately quarterly.

Analyze product, user, transactional, and repayment data to develop risk and underwriting models, reduce losses and fraud, monitor model performance, and guide product and growth strategy. Build Looker dashboards and LookML models, conduct segmentation and experimentation, measure CAC and LTV, and communicate actionable insights to product, engineering, marketing, finance, and leadership.

Build product-level P&L reporting, cost allocation methodologies, financial models, dashboards, and ROI analyses. Partner with Finance, Accounting, Product, and Data teams on budgeting, forecasting, variance analysis, product usage metrics, and investment decisions. Establish standardized reporting rhythms and translate ambiguous business questions into actionable recommendations for senior stakeholders.

Own HR systems, People analytics, reporting, dashboards, data governance, and AI-enabled insights. Partner with People Operations, Finance, Legal, Security, and business leaders to translate workforce questions into metrics and actions. Manage HRIS configuration, integrations, security, automations, data quality, system projects, and annual people cycles. Train managers and People teams while protecting employee data and delivering scalable self-service solutions.

Leads enterprise revenue cycle analytics and strategic performance initiatives, including KPI frameworks, dashboards, reporting, data governance, automation, and performance optimization. Manages and scales an analytics team, advises executives, and partners cross-functionally with Finance, IT, Clinical Operations, and Compliance. Translates complex data into strategies that improve financial performance, throughput, cash flow, compliance, and patient experience.

Leads Marketing's data architecture, metric governance, analytical modeling, predictive modeling, experimentation, and executive performance reporting. Manages three to four analysts while remaining hands-on with advanced SQL, Snowflake data validation, dimensional modeling, cross-system reconciliation, attribution, customer analytics, and AI-assisted natural-language analytics. Partners with engineering, governance, product, and marketing teams to define data products, ensure analytical accuracy, and establish scalable measurement standards.

Build and lead Surescripts’ commercial analytics function, including governed Salesforce and CRM data models, KPI definitions, dashboards, forecasting, pipeline analytics, customer journey insights, automated reporting, quota modeling, and territory planning. Manage an analyst and partner with Sales, Marketing, Finance, Data, and Business Applications. Present actionable recommendations to senior leaders while improving data quality and enabling self-service analytics.

Leads and scales the Growth Product Insights data practice, managing and mentoring data analysts while contributing hands-on analytical work. The role drives proactive insights, experimentation, causal inference, cohort modeling, KPI development, and strategic recommendations for product and growth leaders. It also strengthens data quality and metric governance, partners with engineering teams on complex pipelines and event data, and integrates modern analytics and generative AI tools into team workflows.

Leads financial due diligence and performance analytics engagements for corporate and private equity clients during transactions, integrations, divestitures, and carve-outs. Responsibilities include data extraction, modeling, visualization, forecasting, AI-enabled automation, strategic counsel, client relationship development, team leadership, mentoring, and translating complex findings into actionable recommendations. Requires transaction services, quality of earnings, working capital, cash flow, and advanced analytics experience.

Leads strategic analytics and transformation for sales by developing financial models, forecasts, KPI dashboards, campaign measurement frameworks, and executive reporting. Partners with Sales, Finance, Marketing, and strategic partners to assess performance, improve forecast accuracy, identify growth opportunities, and optimize sales execution. Applies AI, automation, business intelligence, and data-quality practices to streamline reporting and generate actionable insights across revenue, pipeline, bookings, gross margin, and quota attainment.

Own analytics product initiatives from discovery through launch and iteration. Define user needs, prioritize opportunities, write requirements, and collaborate with Engineering, Data Science, UX, and business teams. Use analytics and AI to improve workflows and decision-making while considering data quality, privacy, transparency, and trust. Track adoption and impact to guide ongoing product improvements.

Own the vision, roadmap, and delivery of customer-facing AI, predictive analytics, and SaaS data products. Partner with strategic clients, UX, data science, engineering, sales, and marketing to translate business needs into technical requirements, validate product hypotheses, and launch features that drive adoption, retention, and revenue expansion. Use SQL and data visualization tools to analyze data, communicate insights, and shape intuitive product experiences.

Manages and enhances the organization’s risk management program through complex risk assessments, policy oversight, variance and trend analysis, risk reporting, issue resolution, and escalation. The role works cross-functionally, supports independent assessments, develops risk processes and procedures, and serves as a subject matter expert in a designated risk discipline.

Own GTM performance analytics, KPI and target setting, reporting, forecasting, compensation planning, and performance reviews across Sales and Post-Sales. Identify anomalies and optimization opportunities involving conversion, churn, productivity, pricing, packaging, segmentation, channel economics, and customer quality. Partner with Finance and GTM leaders to develop recommendations, lead strategic initiatives, and ensure data integrity while translating analysis into actionable business decisions.

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.

Leads revenue operations analytics supporting pursuit forecasting, proposal and pricing capacity management, pricing-to-win analysis, pipeline intelligence, executive reporting, capture readiness, and strategic business-system initiatives. The role partners across growth, capture, proposals, pricing, finance, contracts, and delivery to improve resource planning, decision quality, and execution risk visibility throughout the government contracting business-development lifecycle.

Leads marketing and loyalty analytics strategy, measurement frameworks, forecasting, experimentation, campaign reporting, retention analysis, churn modeling, and segmentation. Partners with Marketing and Finance to establish performance goals and translate complex data into actionable recommendations. Automates reporting using analytics platforms, marketing automation tools, experimentation methods, and AI-enabled workflows while identifying opportunities to grow and retain high-value consumers.

Build and maintain people-data pipelines, analytical datasets, metric definitions, dashboards, and self-service data products. Conduct statistical analysis, forecasting, experimentation, segmentation, and predictive modeling to address workforce questions such as attrition, capacity, performance, and productivity. Translate findings into actionable recommendations for leaders while establishing standards for data quality, privacy, documentation, governance, and responsible AI use. Partner across People, Finance, HR Tech, and data teams to shape the analytics roadmap and improve adoption of trusted workforce insights.