Top Entry Level Jobs in NYC, NY

Generate daily valuations for securitized products, model cash flows, analyze market data and asset performance, conduct quality assurance and surveillance, and identify product growth opportunities. The role involves quantitative financial analysis, client communication, and collaboration with trading, research, sales, and technology teams worldwide.

Monitor and analyze market risk across global commodities trading portfolios, explain market movements and P&L drivers, perform stress testing and scenario analysis, and develop risk management strategies. The role leads risk coverage for systematic trading and investor products, prepares reports for senior management, partners with Trading, Finance, and Operations, and improves risk tools, analytics, and automation, including artificial intelligence applications.

Manage end-to-end Payments AI transformation projects, coordinating Product, Technology, and firmwide stakeholders. Lead strategic change initiatives, roadmaps, governance, cross-functional delivery, risk management, success metrics, and implementation. The role requires influencing senior stakeholders, managing complex projects in a matrixed environment, and guiding agile productized delivery. Preferred experience includes AI, payments, data and analytics, data platforms, cloud, and product delivery.

Develops strategic advertising partnerships, launches measurement products, manages campaign execution, creates monetization strategies, and collaborates with sales teams on customer targeting, use cases, and performance measurement. The role supports partnership negotiations, campaign tracking, market positioning, packaging, pricing, and revenue growth for audience insights and measurement solutions.

Build scalable software, data pipelines, analytical infrastructure, and research tools for investment teams. Translate quantitative models and research ideas into reliable production systems, collaborate with researchers, portfolio managers, traders, and engineers, and solve technically challenging data-intensive problems. The role requires strong Python and software engineering fundamentals, experience with complex datasets, communication skills, adaptability, and interest in financial markets.

Conduct innovative machine learning research and develop scalable, robust models for financial markets across asset classes. Apply deep learning, sequence and time-series modeling, natural language processing, large language models, pre-training, fine-tuning, and reinforcement learning to model price formation, market behavior, and risk. Design, implement, optimize, and deploy models using Python and modern machine learning frameworks while collaborating with quantitative researchers, engineers, and traders.

Provide hands-on technical guidance to enterprise customers, supporting product adoption, configuration, and renewal success. Analyze IT operations environments, recommend improvements, advocate for customer goals, conduct business reviews, and collaborate with product, engineering, and technical services teams. The role requires cloud, scripting, CI/CD, containerization, monitoring, and AI-tool expertise, along with up to 20% travel to client sites.

Reports on financial markets, economic trends, investing news, and major stock movements. Writes articles using Morningstar research and data, creates data-driven charts and tables, collaborates with editors to meet deadlines, and trains on Morningstar’s financial information database.

Supports and scales revenue operations across Sales, Marketing, Finance, Legal, and Customer Operations. Responsibilities include improving workflows, maintaining GTM systems and data integrations, supporting deal desk and quote-to-cash processes, managing sales requests, building dashboards, identifying process gaps, and translating business needs into technical solutions. The role requires strong analytical execution, SQL proficiency, cross-functional communication, and comfort working in a fast-paced, fully in-office environment.

Build EliseAI’s product enablement function from the ground up for go-to-market teams. Develop training strategies, curricula, video and e-learning content, webinars, certifications, documentation, and value-based demo programs. Partner with Product, Product Marketing, Sales, and subject matter experts to support launches and improve field readiness. Track proficiency, adoption, utilization, expansion, and NPS metrics, using data and AI to continuously improve enablement programs.

Manage and support the design, implementation, administration, and promotion of employee benefits programs. The role oversees vendor and partner relationships, supports compliant and competitive benefit offerings, coordinates project initiatives and program rollouts, and collaborates with leadership to align benefits with organizational goals. This hybrid position is based at the company’s New York City headquarters.

Leads the design, delivery, and operation of enterprise AI platforms and LLM-based systems. Responsibilities include AI architecture, RAG and fine-tuning, model evaluation, platform development, cloud services, governance, buy-versus-build decisions, cross-team delivery, stakeholder communication, and engineering team leadership and mentorship.

Own the North American People agenda, aligning workforce planning, talent, organizational design, capability building, and leadership development with global strategy. Lead and develop regional HR Business Partners, integrate specialist People functions, support market expansion, and ensure employment-practice readiness across the US, Canada, and Mexico. Serve as a trusted advisor to senior leaders, manage sensitive matters, and represent NAMER in global People decisions. The role is based in New York with travel across North America and to Stockholm.

Own Legora’s legal data strategy by mapping legal sources across jurisdictions, evaluating acquisition opportunities and legal prerequisites, prioritizing datasets, translating legal requirements for engineering teams, and ensuring the quality and accuracy of the legal data layer supporting its global AI legal research product.

Investigate and improve web client performance across page loading, rendering, interaction responsiveness, asset delivery, and caching. Build performance tests, dashboards, and regression guardrails; analyze browser data; ship scoped improvements; collaborate with infrastructure and product engineers; and document performance findings and recommendations.