Top Tech Jobs & Startup Jobs in NYC, NY

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.

Build and maintain auditable data pipelines in Snowflake and dbt to ensure financial reconciliation and audit readiness. Partner with Accounting, Operations, Engineering, and Reporting to investigate data issues, improve integrations via APIs, and own claim reimbursement and contract sales data workflows.

Lead discovery, definition, and delivery of product features for merchants. Drive end-to-end lifecycle from PRDs to launch, use data, A/B testing, and user research, integrate AI where useful, collaborate with engineering and design, gather customer feedback, and prioritize roadmap and sprint activities.

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.

As a Fraud Operations Specialist, you will investigate fraud cases, analyze risk scores, collaborate across departments, and improve fraud detection processes. You will use data analysis to ensure compliance and support the overall efficiency of claims management.

Owns analytics and reporting that inform sales, merchant success, product, and fraud teams; builds business cases, pricing models, dashboards, and ROI analyses to drive merchant acquisition, expansion, and retention.