Top Tech Jobs & Startup Jobs in NYC, NY

Lead data methodology, quality, and accuracy for the Private Investor product. Set data strategy, build QA benchmark sets, author pipeline business logic, apply AI/LLMs for entity resolution and tagging, and scale the data team from an early player-coach to a high-performing organization while supporting customer diligence and trust.

As a Senior Workplace Experience Associate, you will manage facilities, improve processes, oversee vendor relationships, and enhance employee experience in the workplace. This includes planning, compliance, project management, and cross-functional collaboration.

As a Tech Lead, you will own the technical direction of a B2B analytics platform, lead engineering teams, and ensure production reliability while collaborating with various stakeholders to translate business needs into technical solutions.

Assess and evaluate third-party datasets, define success metrics and analytical frameworks, run quantitative analyses, and recommend product opportunities. Support new product development, collaborate cross-functionally with engineering and partnerships, leverage AI/LLMs and automation, and contribute to tooling, knowledge, and operational efficiency.

Lead AI product strategy for investor workflows, designing AI-native products (agents, copilots, MCPs, APIs). Partner with investors, engineers, researchers, and designers to translate LLMs, retrieval, and agent architectures into reliable, production-grade features. Drive rapid experimentation, define evaluation and trust frameworks, and shape platform evolution for investor-grade AI products.

Design, validate, and deploy scalable statistical and distributional models for enterprise consumer analytics. Implement rigorous methodologies, convert ad-hoc analyses into version-controlled analytical libraries, and partner with Data Engineering to optimize performance and scale compute workloads (including cloud/Databricks). Deliver reproducible analytics powering dashboards and LLM-driven applications, with a focus on panel and transaction-level consumer data.

Lead the Central Data Platform roadmap: define and prioritize capabilities, translate business needs into technical requirements, coordinate cross-functional execution, measure adoption and data quality, and drive continuous platform improvements to increase reuse and business impact.

Design end-to-end UX for an AI-powered B2B data product. Translate complex AI and data concepts into intuitive, trustworthy interfaces; conduct user research; define workflows; collaborate with Product, Engineering, and Data Science; contribute to design systems and maintain design quality through launches.

Lead operational management of the Product Classification organization: hire, train, and scale classification and manual QA teams; set metrics, SLAs, and operating cadence; partner with Engineering and Product to improve LLM-driven classification; build processes, rules, and analytic checks to ensure high accuracy at scale.

The Product Manager will define and scale a quant platform for alternative datasets, collaborate with teams to develop product specifications, conduct customer research, and manage go-to-market strategies.