Top Remote Analytics Jobs in Portland, ME

Inovalon seeks candidates to join their Talent Community, emphasizing data-driven solutions to enhance healthcare outcomes and economics.

Lead enterprise data analytics, pipelines, BI, and data governance. Build and monitor ELT/ETL pipelines, develop executive dashboards, define data contracts and domain models, standardize integration patterns, and ensure HIPAA/SOC2-compliant data practices across affiliated entities.

Lead design and implementation of data models, write optimized SQL at scale, enable semantic layers and AI tooling, manage analytics infrastructure, build frontend data surfaces, and partner with product and engineering to structure source systems for reporting.

Hands-on business and delivery analyst who translates stakeholder needs into data integration solutions. Leads current/future-state and gap analysis, requirements, mapping, migration, testing, and delivery coordination. Partners with Operations, Finance, Compliance, and Purchasing to streamline workflows, promote data-driven decisions, and support adoption of analytics and cloud-based tools to improve operational outcomes.

The Lead, Advanced Analytics, Acquisition will analyze data, define metrics, conduct A/B tests, and collaborate with teams to drive growth and insights.

Build and maintain production dbt models on Databricks as the organizations source of truth. Ensure data quality via testing, CI/CD, and documentation. Create Databricks dashboards and semantic metrics, support external reporting, and partner with engineering and analytics teams to turn business problems into durable data products. Drive AI-native workflows using tools like Cursor and Claude Code.

Embed with a single enterprise client to build and edit SQL for audience building and campaigns, design scalable data models, clean and automate pipelines, investigate data discrepancies, and improve workflows to support fast weekly delivery cycles.

The RevOps Analytics Engineer is responsible for maintaining data infrastructure, building reliable data systems, and supporting revenue analytics through effective data modeling and ETL/ELT processes.

Lead a team to develop data strategy and insights across multiple business functions, driving analytics evolution and ensuring data quality and governance.

Own marketing channel performance tracking, reporting, and analysis. Design and analyze experiments (A/B, incrementality), build dashboards in Looker/Tableau, support LTV and forecasting models, identify measurement gaps, and translate analysis into clear recommendations for Growth, Marketing, and Finance stakeholders.

As a Director in the Data & Analytics team, you will lead client engagements, manage projects, develop strategies, create proposals, and mentor team members in data-driven initiatives.

Lead a team of data engineers and analysts, define the data engineering roadmap, oversee data infrastructure, ensure analytics delivery, and establish data governance standards.

The Senior Data Engineer will design, build, and support data environments, orchestrate pipelines, and implement data solutions for advanced analytics and machine learning, working closely with project teams.

Lead the modeling, forecasting, and analytics for go-to-market strategy. Collaborate with Sales and Finance on strategic revenue forecasts and actionable insights.

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.

As a Revenue Analytics Manager, you will own reporting for Sales, Marketing, and Customer Success, build dashboards, automate workflows, and ensure data quality.

Own and improve dbt models, ELT pipelines, and warehouse architecture (Snowflake or equivalent) to deliver reliable executive KPIs and metric governance. Build data spine for Finance/Operations, enforce data quality/testing, partner cross-functionally with Engineering, FP&A, and Accounting, and influence analytics engineering standards, tooling, and roadmap.

Lead global partner analytics and planning for partner GTM motions. Build dashboards, business models, AI-enabled workflows, and executive reports to support partner planning, incentives, coverage, performance management, and cross-functional decision-making across hyperscalers, ISVs, marketplaces, and reseller channels.

Own metrics and datasets that measure cloud, storage, streaming, and ML infrastructure efficiency. Build end-to-end analytics: metric frameworks, pipelines, dashboards, and narratives that inform executive and engineering investment decisions. Pioneer methods to quantify AI and agent-driven productivity, identify efficiency opportunities, and partner with data engineers and data scientists to deliver trusted, reusable insights and recommendations.

Lead analytics strategy and portfolio measurement for payor-focused products. Define standards for actuarial value, client reporting, and internal measurement. Align cross-functional teams (actuaries, product, reporting, analytics) on priorities, requirements, and sequencing. Develop measurement frameworks, value stories, and reporting approaches to improve comparability, decision-making, and portfolio-level impact.

Hands-on Adobe Customer Journey Analytics (CJA) Lead responsible for designing, configuring, and executing CJA solutions, enabling AEP data flows, defining measurement frameworks, mapping data sources, and delivering reporting while partnering with stakeholders and providing technical architecture and execution.

Lead revenue planning, forecasting, and revenue-science for GTM. Build propensity, churn, and expansion models; operationalize models into workflows. Own AOP, quota setting, capacity modeling, territory design, data warehouse strategy, identity resolution, TAM/segmentation, and pilot AI tools to automate analytics and seller/CSM workflows. Serve as single source of revenue truth for Sales, Customer Success, and executives.

Manage design, development, and delivery of data products and analytics solutions. Lead and coach an analytics team, gather requirements, improve processes, reduce technical debt, collaborate with platform and product architecture, and ensure solutions meet internal and external client needs.

Lead infrastructure analytics for compute, storage, and networking: design scalable data pipelines, define core metrics, build dashboards and APIs, ensure data quality and governance, drive instrumentation fixes, and advise executives on capacity, utilization, and readiness.

Lead sales analytics and planning for Consumer and Fleet channels. Build MQL-to-SQL frameworks, CRM infrastructure, lead scoring, forecasting models, and executive dashboards. Partner cross-functionally with Marketing Analytics, IT, and Sales to ensure data governance, reporting cadence, and scalable sales intelligence.