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

Develop and scale monitoring, anomaly detection, dashboards, and analytical frameworks for Personal Lines Auto pricing programs. Analyze large datasets to identify data-quality issues, emerging trends, root causes, and program risks. Automate reporting and reduce manual effort while partnering with data, technology, underwriting, risk analytics, and product teams. Communicate monitoring results and actionable recommendations to technical and business stakeholders.

Senior BI Platform Administrator to own enterprise BI infrastructure across Power BI, Microsoft Fabric, and Snowflake. Responsibilities include federated Power BI governance, Fabric AI Agent skill design and deployment, RBAC/RLS design, certified semantic model development, CI/CD and SRE practices for platform reliability, and measuring adoption. Partners with Data Engineering, IT Security, AI/ML, and business stakeholders to drive secure, performant analytics and AI-powered experiences.

The Senior Data Engineer will design and implement data processing pipelines using Java and Spark, optimize performance, and mentor junior engineers while ensuring compliance with data governance standards.

The Senior Analyst in AML KYC will conduct detailed customer onboarding, monitor client relationships for compliance, and update KYC records while utilizing AI tools for efficiency.

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.

The Senior Data Analyst gathers BI requirements, analyzes enterprise and offline datasets, writes and optimizes SQL queries, and builds dashboards using Power BI, Tableau, and Domo. The role translates business needs into technical specifications, designs dashboard wireframes, validates data, documents processes, and collaborates with engineering, product, and business teams. Knowledge of the US trust business is essential for interpreting data within financial and regulatory contexts.

Lead product vision and execution for internal, data-intensive technical initiatives. Improve and future-proof datasets, shared services, and platforms. Partner across engineering, data science, analytics, and product to translate needs into requirements, prioritize work, drive cross-functional delivery, define success metrics, and communicate roadmap and risks to stakeholders.

Manage a team of data scientists to develop fraud detection models, lead planning and collaboration with leadership, and communicate outcomes effectively while maintaining strong business intuition and technical leadership.

Lead and build a product analytics function: define KPI framework, instrumentation, and self-serve analytics using Pendo and BI tools. Partner cross-functionally to measure product performance, surface insights, influence roadmap and embed AI-powered analytics into product lifecycle.

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.

Lead design and operation of large-scale data pipelines and data APIs. Build Spark/PySpark workflows on Databricks, optimize job performance, manage data quality and observability, and develop MCP servers and AI-agent integrations. Mentor engineers, define standards, support production incidents and on-call rotations, and collaborate with stakeholders to deliver scalable data platform products.