Data Analyst Jobs in Cambridge, MA

The analyst collaborates with investment teams to deliver data solutions, improve data quality, build analytical tools, generate reports, and drive process improvements within investment consultancy and oversight.

Maintain and evolve GMO's security master and portfolio data platforms (NeoXam DataHub, Aladdin, Eagle PACE). Analyze large datasets using Python, SQL, and Excel to identify data quality issues, define business requirements, support conversions/migrations, implement controls/automation, and collaborate with stakeholders to modernize data validation and onboarding processes.

Lead end-to-end analytics and data product work for Employee and Corporate Finance domains: source system discovery (notably Workday), source-to-target mapping, curation into a unified data model, stakeholder partnership, prototyping with code and visualizations, backlog ownership, and ongoing validation and support of business-facing data products.

Lead development of customer-facing analytics and internal dashboards by building advanced SQL models, data transformations, and visualizations. Collaborate in Agile team ceremonies, prioritize work, improve processes, validate analyses, and present actionable insights to stakeholders and senior leadership.

Lead analytics and operational insights for Customer Operations: define core metrics, build dashboards and forecasts, model churn/renewal risk, enable self-serve reporting, implement AI-enabled automation, and partner cross-functionally to drive retention, expansion, and support efficiency.

Partner with stakeholders to define metrics and deliver dashboards and insights. Build and optimize data models in Amazon Redshift, design and maintain scalable ETL pipelines using Python and Apache Airflow, monitor data quality and pipeline performance, and participate in code reviews and engineering best practices to support analytics and reporting needs.

Lead business and systems analysis for data migration and automation initiatives. Translate requirements into epics and user stories, perform data extraction/mapping/reconciliation, and validate data across platforms (Informatica→Databricks). Support QA/UAT and release cycles, enhance automation frameworks (Selenium, Cypress), and apply AI-driven QA techniques for intelligent test generation and anomaly detection while collaborating with stakeholders and engineering teams to drive delivery.

Partner with Marketing, Conference, and Membership teams to build reporting frameworks, measure campaign ROI and attribution, analyze funnels and cohort/LTV metrics, develop dashboards in Tableau, run SQL analyses on Snowflake, support experimentation, and deliver executive insights to drive acquisition, engagement, retention, and revenue growth.

Support research and product development on large electric loads (data centers, advanced manufacturing). Vet data sources, drive AI-enabled data tools, track policy and projects, produce client reports, support clients and consulting engagements, and coordinate cross-team projects involving research, product, and data teams.

Audit and ensure quality of data labeling outputs, coach and onboard Data Labeling Associates, provide actionable feedback, monitor workflows, identify patterns and edge cases, and help improve guidelines and processes in human-in-the-loop AI workflows.

Audit and validate data labeling outputs, provide structured feedback and hands-on training to annotators, monitor workflows and escalate issues, help apply and improve guidelines, and identify patterns in human and model outputs to maintain high-quality AI training data.

Audit and review data labeling outputs, provide actionable feedback, train and support labeling teams, monitor workflows, identify recurring issues and edge cases, participate in calibrations and stakeholder syncs, and help improve guidelines and processes in human-in-the-loop AI workflows.

Audit and ensure quality of labeled data by reviewing DLA outputs, providing feedback and coaching, supporting onboarding and training, monitoring workflows, identifying recurring issues and edge cases, and contributing to guideline and process improvements in human-in-the-loop AI workflows.

Audit and improve data labeling quality in human-in-the-loop ML workflows. Coach and onboard labelers, provide actionable feedback, monitor queues, identify recurring issues, and help refine guidelines and processes.

Audit and ensure quality of data labeling outputs, coach and onboard annotators, enforce and improve guidelines, identify recurring issues and edge cases, escalate risks, and document feedback to support human-in-the-loop AI workflows.

Audit and ensure quality of data labeling outputs, coach and onboard annotators, apply and refine guidelines, monitor workflows and escalate issues, document findings, and support human-in-the-loop AI evaluation processes.

The Workday System Analyst is responsible for maintaining Workday data structures, configuring business processes, conducting data audits, and supporting system integrity and availability efforts.

Analyze and validate large benchmarking datasets, improve methodologies, support product enhancements, and engage directly with clients and sales to drive adoption and inform product strategy.

Validate and assure enterprise data quality across source systems, ETL/ELT pipelines, data warehouses, and reporting. Investigate production incidents, design test strategies and automated validation, perform regression and non-functional testing, analyze data quality metrics, support compliance/audit activities, and collaborate with engineering and business stakeholders to improve data governance and controls.

Audit and monitor data labeling outputs, provide actionable feedback, support onboarding and training of annotators, enforce and improve guidelines, escalate workflow issues, and document findings to maintain high-quality human-in-the-loop AI data processes.

Senior Addepar data engineer/analyst responsible for supporting and scaling Addepar integrations, building and maintaining data pipelines (Addepar↔Snowflake/Canoe/other platforms), diagnosing and resolving data quality issues, developing SQL-based reconciliations and automation, partnering with business and technology stakeholders, and supporting production operations, governance, testing, and documentation for wealth and asset management data.

Lead Wellington's market data program, managing vendor relationships, contract negotiations, onboarding/renewals, inventory and invoice workflows, licensing/reporting compliance, budgeting, and system improvements (Optimize Spend, ServiceNow). Provide stakeholder support, training, and drive process improvements to maximize value and control costs.

Audit and ensure quality of data labeling work for ML using human-in-the-loop processes. Provide feedback, train and support annotators, monitor workflows, identify recurring issues, and help improve guidelines and processes.