Top Tech Jobs & Startup Jobs in Boston, MA

Lead and manage a remote analytics engineering team responsible for Extend’s Snowflake warehouse, dbt repository, ingestion pipelines, data models, monitoring, and quality standards. Oversee hiring and development, architecture, platform migrations, reliability, incident response, documentation, and self-service analytics. Partner with actuarial, risk, fraud, product, finance, and operations teams to establish trusted shared data definitions and prioritize platform improvements.

Manage growth strategy and strategic relationships for Extend’s largest enterprise merchants. Responsibilities include optimizing account performance, conducting executive business reviews, driving product adoption, managing promotional budgets, developing long-term business plans, and identifying ROI opportunities through data. The role also gathers customer feedback for product roadmaps and collaborates with risk, analytics, marketing, product, and operations teams. Travel to client sites is estimated at 15–20%.

Build and maintain invoicing, reimbursement, revenue recognition, claims, and financial reporting models using SQL and dbt. Reconcile merchant, operational, warehouse, and accounting data; investigate variances; validate expenses; and establish automated financial controls. The role also triages data issues, investigates production APIs, supports audits, partners on merchant configuration, and drives upstream fixes through root-cause analysis and automation.

Leads financial systems engineering for a service-contract business. Owns reconciliation systems, invoicing logic, financial data models, revenue recognition controls, and audit reporting. Manages SQL and dbt models, automated validations, exception resolution, merchant configuration audits, and cross-functional escalations across Engineering, Finance, Accounting, and Revenue teams. Leads individual contributors and develops the team as business needs evolve.

Provide day-to-day legal support for a fast-paced tech company: draft and negotiate commercial contracts, advise cross-functional teams (revenue, product, HR, finance, engineering), assist corporate governance and board preparations, support public company readiness, oversee global corporate administration and compliance, and help scale the legal function.

The Lead Risk Analytics Data Scientist will develop risk pricing, design data models, automate workflows, and communicate insights to leadership. Responsibilities include owning the risk narrative, building analytics foundations, and utilizing AI to enhance efficiency.

Optimize People processes through AI adoption, workflow redesign, process documentation, and cross-functional implementation. Own workforce metrics, HRIS data accuracy, dashboards, surveys, workforce planning, attrition and compensation analyses, and leadership reporting. Partner with People Operations, HRBPs, Recruiting, and business leaders to improve employee experience, data governance, privacy compliance, and AI adoption across the company.

Lead a team analyzing large-scale behavioral and transactional data to detect and prevent fraud. Build monitoring frameworks, dashboards, and metrics; track and optimize AI agent performance; partner with ML, product, and engineering to translate findings into model features; hire, mentor, and coach analysts; and define cross-functional fraud strategies.

Lead company-wide People programs, advise executives on org design and succession planning, optimize HR processes with data and automation, drive performance management, compensation, leadership development, manager enablement, and employee engagement while mentoring the People team and ensuring compliance.

Lead and build the Risk Analytics function: define pricing methodology and risk frameworks, own portfolio and pricing strategy, convert monitoring into decision systems, architect the Risk Analytics data layer (dbt/Snowflake), mentor senior data scientists, and represent risk recommendations to senior leadership to drive business decisions.