Top Remote Analysis Reporting Jobs in Portland, ME

This role drives data-driven decision-making in product analytics, collaborating with cross-functional teams to generate actionable insights and evaluate new launches to enhance platform growth.

Gather and document business and functional requirements, analyze processes, recommend improvements, produce BRDs/FRDs/user stories and process maps, support solution design, UAT, testing and deployment, produce reports/dashboards, monitor project progress, and support change management and stakeholder communication.

Owner of the analytics foundation: design and maintain BigQuery/dbt models, pipelines, and Looker Studio reporting; build AI workflows and web apps on GCP; integrate marketing, e-commerce, and fulfillment data; ensure GCP ops, security, and reliability; use AI-assisted tools daily and collaborate with business and client stakeholders.

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.

Deliver sales reporting, data preparation, dashboard updates, and analysis to support sales intelligence. Maintain data accuracy across the warehouse and CRM, build Power BI visuals, execute ETL processes, and translate insights for non-technical stakeholders.

Manage analytical service operations by overseeing a team, designing software for data mining, developing statistical models, and generating insights for marketing outcomes. Provide training and mentorship to direct reports.

Lead CX analytics strategy and operations by standardizing metrics, enabling self-service analytics, and embedding AI in the analytics lifecycle to enhance decision-making processes.

Lead the enterprise data platform strategy and architecture, driving Snowflake/dbt-based platform evolution, self-service Data Mesh and medallion models. Build AI-ready pipelines, RAG systems, and observability/cost frameworks while managing a central data team, supporting federated BI, and executing hands-on technical work.

Use advanced analytics and ML to design and monitor credit risk models, optimize underwriting and credit strategies, partner with Engineering/Product/Compliance, oversee portfolio performance and regulatory alignment, and lead cross-functional initiatives to balance growth, compliance, and risk mitigation.

The Principal Data Scientist will lead data analysis projects, collaborate with product management, assess business impacts, ensure data governance, and mentor junior analysts. Must leverage statistical techniques and machine learning to drive product strategy and business outcomes.