Top Remote Analytics Manager Jobs

The Product Manager will lead growth initiatives, run experiments, build dashboards, investigate metrics shifts, and maintain product documentation, aiming to enhance user engagement and retention.

Manage complex consulting projects for Veeva customers in analytics, focusing on project delivery, client relationships, and business development.

Lead AI adoption and enablement across the business by building capability, governance, and reusable patterns; design and operationalize agentic AI solutions, copilots, and human-in-the-loop workflows; partner cross-functionally to prioritize, scale, and embed AI into analytics, processes, and platforms while measuring adoption and business impact.

Lead analytics-focused product work: define vision, scope, and roadmaps; write user stories and requirements; manage sprints and stakeholders in Jira; support analytics teams to deliver scalable, high-impact data products for healthcare value-based care.

Define and drive product strategy for agentic data analytics in the datacenter: connect agent workflows, text-to-SQL, semantic context, query execution, and intelligent workload routing. Engage customers and partners, set success metrics (latency, cost, correctness, utilization), collaborate cross-functionally on architectures and blueprints, and present vision and progress to internal and external stakeholders.

Lead the product strategy for Loop's Competitive Intelligence module, integrating external intelligence into strategic portfolio decisions, and collaborating with cross-functional teams to enhance competitive positioning.

As an Engineering Manager, you'll lead a remote team, manage MLOps projects, ensure high performance, and mentor engineers while driving product strategies.

This role leads Revenue Growth Management initiatives, linking data analytics with executive strategy to drive business growth through actionable insights and project management.

Lead e-commerce analytics to drive commercial impact: build used dashboards, analyze acquisition/retention/funnel/channel performance, ensure tag/data-layer integrity (Tealium iQ), support A/B testing, and present actionable insights to stakeholders to grow online revenue.

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.

Lead a small data engineering team partnering with Engagement Marketing to build scalable ETL/ELT pipelines, ensure data quality, define marketing metrics, integrate trusted data with ad platforms, and drive the data roadmap to enable measurement and growth.

Lead support analytics, KPI framework, QA, workforce management, capacity planning, and knowledge/content operations. Build dashboards, translate data into leadership decisions, drive process improvements, and oversee WFM and QA programs across voice, chat, and AI channels.

Manage CVS Enterprise Finance's reporting strategy, execute standardized reporting, collaborate with stakeholders, drive automation, and deliver reporting initiatives.

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.

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 credit risk analytics for credit card and personal loan portfolios: develop ML-driven credit strategies, monitor portfolio performance, run A/B tests, forecast credit losses and stress tests, ensure regulatory compliance, and partner across Product, Engineering, Legal and Marketing.

The Senior Manager of Customer Analytics leads a team managing client analytics projects, ensuring timely deliverables, and enhancing data methodologies using various analytical tools.

Lead the vision and delivery of customer-facing AI/ML models and data products. Partner with clients, data science, and engineering to define requirements, validate hypotheses with SQL-driven analysis, design data visualizations, and launch features that drive adoption and ARR.

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

Lead a team of analysts to advance fraud and safety operations through analytics, ensuring robust data products and compliance while empowering stakeholders with actionable insights.

Lead a team of ~7 data scientists to deliver timely, accurate product analytics and experimentation insights; manage people, mentor staff, partner with product and engineering, and build accessible data products and measurement practices.

Lead product-focused data science workstreams to drive product decisions, experimentation, forecasting, segmentation, and AI-enabled analytics. Partner cross-functionally to define metrics, build dashboards, translate findings for stakeholders, and ensure governance and scalable measurement frameworks that improve product performance and revenue.

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 and mentor a team of data analysts while remaining hands-on with SQL and BI tools. Partner with business leaders to translate goals into data requirements, deliver high-impact analyses and presentations, and recommend operational changes across marketing, call center, and clinical operations.

Lead measurement strategy for paid and performance marketing, design and interpret A/B and lift tests, run incrementality and attribution analyses, and optimize channel budgets. Build business cases, develop dashboards and BI workflows, evaluate AI-enabled analytics tooling, and enable self-serve analytics. Partner cross-functionally and present insights to leadership to drive experimentation, growth, and LTV outcomes.