Top Senior Data & Analytics Jobs in Portland, ME

Leads the strategy, development, and delivery of client-facing reporting and analytics solutions for life sciences clients. Manages dashboards, automated reporting, self-service analytics, KPI standards, data governance, and reporting platforms using Power BI, SQL, Microsoft Fabric, and related tools. Translates commercial, medical, operational, claims, and prescription data into actionable insights while supporting client onboarding, executive readouts, project delivery, vendor performance, budgets, and cross-functional stakeholder collaboration.

Own risk analytics initiatives that improve repayment rates, optimize collections costs, monitor trends and emerging risks, and evaluate external agency performance. Partner with stakeholders and vendors to develop actionable insights, support strategic decisions, and apply AI tools to automate reporting and improve collections outcomes. The role requires advanced SQL and experience in credit risk, fraud risk, collections, or related lending analytics.

Performs complex commercial insurance data analysis, develops business recommendations, improves reporting processes, communicates insights to partners and senior management, and supports strategic initiatives. The role requires strong statistical, analytical, coding, and data visualization skills, along with insurance knowledge, cross-functional collaboration, mentorship, and occasional travel.

Designs and scales cloud-native data platforms and ingestion pipelines using AWS, Databricks, and Spark. Builds APIs, file-upload mechanisms, ETL/ELT workflows, data transformations, and Lakehouse architecture supporting analytics, machine learning, and operational use cases. Provides operational support for legacy C# .NET ingestion processes, troubleshoots pipelines, and promotes data governance, security, reliability, and documentation in a multi-tenant SaaS environment.

Manages the enterprise Data Governance and Analytics Center of Excellence, leading staff, governance initiatives, analytics strategy, maturity modeling, budgets, vendors, and planning. Coordinates data quality, stewardship, privacy, acquisition, and release programs while partnering with data scientists, engineers, technology governance teams, and business stakeholders. Develops executive presentations, aligns enterprise definitions and algorithms, establishes standards, and ensures analytics projects and business cases meet organizational objectives and deadlines.

Design, build, and lead a scalable, configuration-driven data integration platform. Improve performance, automate monitoring and deployments, provide escalated support, and collaborate across product and engineering to deliver reliable, secure data integrations.

Build and own workforce capacity, forecasting, and scenario models that guide hiring, coverage, account assignments, and organizational design. Maintain executive-ready dashboards and real-time visibility into workforce supply, demand, hiring pipelines, utilization, attrition risks, and workload distribution. Partner with HR, Finance, Revenue Operations, and business leaders to translate complex workforce data into actionable decisions and ensure consistent reporting and assumptions across systems.

Serves as a strategic analytics partner to Marketing, owning funnel, attribution, ROI, account scoring, experimentation, and pipeline analytics. Builds scalable datasets, dashboards, and quality controls while connecting customer, campaign, product usage, CRM, and revenue data. Delivers executive-ready reporting, QBR insights, and recommendations that improve conversion, marketing investment effectiveness, account-based marketing, product adoption, and pipeline growth.

Design and maintain scalable ETL/ELT pipelines, analytical dashboards, and reporting tools supporting clinical, research, and operational priorities. Write production-quality Python, R, and SQL; develop data architecture; partner with data scientists to operationalize analytics; integrate AI-enabled workflow improvements; establish engineering standards; and mentor junior team members.

Analyze complex financial and business data to guide planning, forecasting, investment decisions, and strategic growth. Partner with FP&A, Accounting, RevOps, Product, Marketing, Data Engineering, and analytics teams; automate recurring workflows; build self-service dashboards and data assets; improve analytics infrastructure; and communicate actionable insights to technical and non-technical stakeholders.