Top Remote Analytics Jobs in Boston, MA

Lead growth analytics for Zendesk’s product-led growth motion, guiding a team of analysts and partnering with Product, Engineering, Sales, Marketing, and Data teams. Define funnel metrics, measurement plans, experiments, and instrumentation across acquisition, activation, conversion, retention, and expansion. Analyze customer behavior using segmentation, cohorts, funnels, experimentation, and statistical methods. Improve self-service reporting, dashboards, metric definitions, reusable datasets, and analytics capabilities while coaching analysts and influencing senior stakeholders.

Supports DIRECTV FOR BUSINESS through KPI analytics, financial analysis, customer segmentation, and process improvement initiatives. The intern analyzes performance drivers, commitments, projects, and customer experience impacts; synthesizes insights into data stories; documents processes; and presents findings to leaders. The role involves cross-functional virtual collaboration and requires proficiency in Excel, PowerPoint, Python, SQL, Power BI, and data visualization.

Leads and develops a team of Conversion Data Analysts, owning workload prioritization, delivery quality, and performance outcomes. Uses KPIs and data to identify risks, guide decisions, and improve high-volume conversion workflows. Partners with project management, Engineering, Product, Support, and leadership to ensure accurate data mapping and successful customer onboarding. Requires people leadership, SQL, Excel, data validation, CRM, and conversion tooling experience.

Leads the design and delivery of scalable analytics solutions using Azure Databricks, Power BI, and related platforms. Transforms and validates structured and unstructured data, applies statistical techniques, develops dashboards and analytical models, and implements data governance and quality processes. Partners with business and technology stakeholders to translate requirements into technical solutions, provides peer guidance, monitors data trends, and communicates actionable insights to technical and non-technical audiences.

Lead the firm’s analytics strategy, roadmap, and growing analyst team. Partner with executives and law firm operations leaders to define KPIs, evaluate performance, identify bottlenecks, build forecasting and predictive capabilities, and translate data into business actions. Guide SQL, Python/R, statistical modeling, visualization, data quality, and analytics infrastructure standards while partnering with technology and data engineering teams to embed insights into operational workflows.

Own the digital measurement ecosystem across websites, quote engines, customer portals, and account applications. Lead Google Tag Manager tracking frameworks, data-layer standards, Google Analytics 4 configuration, conversion events, attribution, funnel analysis, experimentation measurement, data-quality audits, and analytics governance. Partner with Marketing, Product, Engineering, and Data teams to translate customer behavior into actionable insights that improve growth, conversion, and customer experience.

Leads College Board’s Operations analytics strategy and team, developing forecasting, predictive modeling, optimization, cost assessment, and decision-support capabilities. Partners with senior leaders across Operations, Product, Program, Technology, and Finance to improve execution, customer experience, efficiency, and cost savings. Responsibilities include setting technical direction, embedding analytics into operational decisions, presenting insights, hiring and coaching analytics staff, and building future AI and data-infrastructure capabilities.

Analyzes healthcare claims, pharmacy, laboratory, financial, utilization, and risk-adjustment data. Develops suspect, targeting, tracking, QA, and reporting systems for Medicaid, Marketplace, Medicare, and MMP interventions. Performs predictive modeling, statistical analysis, forecasting, anomaly detection, data validation, root-cause analysis, and risk-score tracking. Communicates analytical findings to technical and nontechnical stakeholders while supporting cross-functional projects and regulatory or business requests.

Leads internal data analysis projects, identifies business opportunities and risks, delivers strategic insights to leadership, manages junior analysts, develops dashboards, and improves data quality across company platforms. The role requires translating quantitative findings for nontechnical audiences and applying healthcare or pharmaceutical dataset experience to strategic decision-making.

Own client-facing analytics strategy and implementation across GA4, Adobe Analytics, tagging, measurement frameworks, dashboards, experimentation, and GEO measurement. Audit and QA analytics implementations, define KPIs, evaluate incrementality and causal relationships, present executive-ready insights, and collaborate with SEO, paid media, creative, data, engineering, and client teams. Build AI-assisted workflows, automations, scalable tools, and dashboards while mentoring teammates and managing multiple client workstreams.

Conduct quantitative research for traders by testing market hypotheses, building and maintaining documented signals, performing event studies and backtests, and validating results against leakage, survivorship bias, transaction costs, and regime dependence. Organize reproducible point-in-time datasets, communicate findings clearly, track signal performance, and use AI tools to accelerate research and coding while verifying outputs.

Own enterprise analytics audits, implementations, data quality, attribution, segmentation, SQL analysis, BI dashboards, experimentation measurement, and client reporting. Serve as the senior analytics partner for major accounts, present insights to executives, train client and internal teams, and help define analytics and experimentation services. The role requires hands-on Adobe expertise, autonomous prioritization, technical collaboration, and the ability to connect organic and AI search performance to pipeline and revenue.

Lead people-analytics strategy for Talent Acquisition and Talent Development. Drive end-to-end analysis of complex workforce problems, deliver evidence-based recommendations to senior leaders, ensure data governance and quality, coach junior analysts, build metrics frameworks, and conduct benchmarking and external research to inform workforce strategy.

The Lead Risk Analytics Data Scientist will develop risk pricing, design data models, automate workflows, and communicate insights to leadership. Responsibilities include owning the risk narrative, building analytics foundations, and utilizing AI to enhance efficiency.

Lead MyFitnessPal’s product analytics practice and team, advising the Chief Product Officer and senior leaders through actionable data insights. Define product metrics, oversee experimentation, analyze customer and marketing behavior, improve instrumentation and data infrastructure, and shape product strategy, roadmaps, engagement, and retention. This hands-on director role combines executive communication, team development, analytical leadership, and direct analysis across consumer iOS and Android applications.

Own end-to-end product and customer analytics across financial product experiences. Define meaningful metrics, analyze complex datasets with SQL, connect customer behavior to business outcomes, and translate qualitative feedback into product insights. Partner with product, engineering, research, data science, and CX teams to influence roadmaps and senior leadership decisions. Use AI tools such as Cursor and Claude to accelerate analysis and automate workflows.

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 Senior Data Scientist will design and deploy time-series forecasting models, collaborate with stakeholders, and operationalize models in cloud environments, focusing on demand planning across various industries.

Lead payments analytics by building scalable reporting, causal inference and ML models, designing experiments, partnering with product/engineering/finance to optimize payment processing, reconciliation, and settlement, and translating results into executive recommendations to drive global payments improvements.

Lead implementations and ongoing analytics consulting for community health centers: extract, clean, and analyze EHR data (heavy SQL), build reports and visualizations, manage projects and stakeholders, train client data teams, and inform product improvements based on customer feedback and domain expertise.