Top Tech Jobs & Startup Jobs in NYC, NY

Supports Private Client Advisors by processing account openings, money movements, trades, client requests, account reviews, performance reports, and wealth-planning activities. Maintains client relationships, promotes firm services, manages referrals and leads, follows Know Your Customer and risk-management procedures, completes compliance documentation, prioritizes workflows, meets deadlines, and contributes to a positive team environment.

Owns product discovery, strategy, roadmap development, customer journey optimization, and measurement for small-dollar lending products. Partners with Product Development, Risk, Design, and other teams to improve acquisition funnels, customer experience, approval rates, and origination volume. Conducts market research, creates process maps, develops measurement frameworks, and analyzes lending marketing campaigns and performance data to guide product recommendations.

Leads climate physical risk modeling and analytics initiatives within JPMorgan Chase’s Risk Management organization. Develops climate risk metrics, scenarios, and macroeconomic impact analyses; integrates physical risk data into financial risk models; coordinates data, technology, and modeling teams; delivers executive-level insights; manages stakeholders; and mentors junior staff. The role supports climate resilience, low-carbon transition planning, regulatory requirements, and innovative methodologies for assessing climate, nature, and social financial risks.

Leads the design, experimentation, productionization, and optimization of machine learning, deep learning, generative AI, LLM, and agentic systems. Develops Python-based proofs of concept and production solutions, evaluates and tunes models, integrates generative AI into ML platforms, improves system performance, and partners with product and engineering teams. Acts as an ML subject matter expert while mentoring practitioners and influencing product and technical decisions.

Owns the end-to-end lifecycle of approved investment trades, including pre-trade analysis, trade planning, execution coordination, allocation validation, exception management, and post-trade review. Partners with investment, trading, operations, and client-facing teams while maintaining risk controls, fair allocation, and best execution standards. Leads initiatives to improve portfolio implementation efficiency, overlay management, costs, workflow scalability, and client outcomes.

Develop and execute cyber threat intelligence strategies, analyze large datasets to identify threat indicators, validate AI-assisted intelligence outputs, and translate findings into actionable recommendations. The role collaborates with stakeholders, improves detection frameworks and response playbooks, supports cybersecurity operations, and communicates intelligence to senior executives. Preferred experience includes SOC or Cyber Fusion Center environments, threat intelligence frameworks, regional expertise, language skills, and collaboration with government or industry threat-sharing communities.

Leads enterprise AI governance product strategy and transformation across the AI/ML lifecycle. Owns roadmap, delivery, adoption, lifecycle governance, and measurable outcomes while translating policies and control frameworks into scalable self-service products. Partners with engineering, risk, legal, compliance, privacy, cybersecurity, data governance, and business teams to modernize legacy processes, enable responsible AI, and align executives on priorities and trade-offs.

Leads credit card acquisition analytics for U.S. consumer and small business portfolios. Manages data scientists and analysts, develops predictive models, evaluates marketing campaigns, shapes offer and targeting strategies, and translates customer and channel insights into measurable business outcomes. Partners with product and marketing leaders, communicates findings to senior stakeholders, and promotes experimentation, model governance, scalable reporting, and continuous improvement.

Designs, develops, experiments with, and productionizes machine learning, deep learning, and generative AI solutions. Builds LLM and agentic workflows, conducts model tuning and evaluation, optimizes system performance, and develops end-to-end Python solutions. Partners with product and engineering teams to integrate generative AI into scalable ML platforms and production services, with a focus on NLP, RAG, embeddings, inferencing, and MLOps.

Leads development of an enterprise Agent SDK and agentic AI platform. Designs production-grade agent capabilities, evaluation systems, model-serving workflows, retrieval-augmented generation, and tool-using agents. Writes code, optimizes performance, establishes engineering standards, and partners across product, data, platform, and application teams. Requires extensive experience building large-scale machine learning systems, cloud and Kubernetes workloads, and reliable generative AI solutions.