Top Remote Senior Level Data & Analytics Jobs in Boston, MA

Own the roadmap and backlog for insurance pricing tools, gather requirements, coordinate delivery, and develop scripts and processes across rating programs. Analyze premium mismatches, maintain SAS pricing tools, conduct pricing analyses and quality checks using Python, SAS, Excel, and related technologies. Collaborate with cross-functional teams, resolve defects, present findings, train colleagues, and support successful pricing model rollouts.

Designs and maintains business intelligence tools, dashboards, and data extraction processes. Performs source-system analysis, data profiling, ETL, data mapping, transformation-rule definition, testing, and dashboard performance troubleshooting. Uses SQL, Tableau, Alteryx, R, Python, SAS, Google Analytics, and Adobe Analytics to generate insights, predictive models, and reporting. Collaborates with business users and operations teams on user acceptance testing, deployment, and process improvements. The role is fully remote within the United States.

Lead RevOps data modeling, ETL/DBT development, and dashboarding to ensure high-quality revenue data. Build Snowflake data marts, author complex SQL, create Tableau visualizations, apply AI/ML forecasting, and partner with Sales, Marketing, Finance, and IT to resolve data quality and reporting issues.

Lead revenue analytics by developing business cases, dashboards, KPI frameworks, experiments, and automated analytics solutions. Partner with client success, marketplace, merchants, and cross-functional teams to evaluate performance, guide go-to-market decisions, quantify product value, and scale data-driven execution. Serve as the analytics subject matter expert while translating structured and unstructured data into actionable recommendations and compelling stakeholder narratives.

Lead end-to-end analytics for major platform partnerships, identifying growth opportunities and informing product, investment, risk, and pricing decisions. Conduct complex analyses, design experiments, build scalable data models, metrics, dashboards, and AI-assisted workflows, and translate findings into business recommendations. Partner cross-functionally with Product, Engineering, Finance, Revenue, and Strategic Partnerships while mentoring analysts and improving analytical practices.

Lead customer listening and Voice of Customer programs, including NPS, CSAT, CES, surveys, and interviews. Analyze qualitative and quantitative customer data to identify drivers, trends, pain points, and opportunities. Present insights to executives and cross-functional teams, facilitate action planning, and drive systemic customer experience improvements. Evaluate AI tools for sentiment analysis, theme extraction, and customer research while helping build a data-driven, customer-centric culture.

Lead end-to-end COGS and gross margin analysis for hardware and software products, model cost-saving scenarios, answer ambiguous executive questions, partner with data engineering/finance/product, build reliable datasets and analytical frameworks, and present recommendations to C-suite stakeholders.

Own the enterprise reporting strategy and Sigma BI platform, including administration, governance, security, data modeling, dashboard development, and self-service reporting. Partner with business and analytics teams to define KPIs, create root-cause reporting frameworks, connect operational metrics to business outcomes, and improve reporting consistency. Lead Sigma adoption through training, documentation, standards, and mentorship while integrating modern data and AI technologies.

Serves as an enterprise architecture subject matter expert within a DoD environment. Supports DoD Business Enterprise Architecture initiatives, business process alignment, enterprise strategy, stakeholder analysis, requirements documentation, reporting, and project activities using MEGA HOPEX and Microsoft Office tools.

Leads and develops a Data Platform engineering team while owning delivery of complex data initiatives. The role establishes delivery discipline, assesses technical and implementation risks, partners cross-functionally, and drives production reliability, data quality, observability, incident management, and on-call readiness. It also guides the evolution of scalable data ingestion, transformation, lakehouse, cloud architecture, governance, and reusable platform capabilities.

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.