Evercore-posted 3 months ago
$150,000 - $170,000/Yr
Full-time • Mid Level
New York, NY
Securities, Commodity Contracts, and Other Financial Investments and Related Activities

Evercore's Private Capital Advisory (PCA) team is a leading global secondaries market advisor, focusing on providing strategic advisory services to financial sponsors across a variety of portfolio and fund management objectives, advising limited partners on liquidity solutions for their private asset portfolios, and employing various forms of structured ABS technologies to create innovative capital and liquidity solutions for private markets issuers and investors. PCA is seeking to hire a highly motivated Quantitative Analyst to support senior team members in applying advanced data-driven techniques to business and financial challenges. The ideal candidate has strong technical and analytical skills, a foundation in data science or machine learning, and a desire to learn and grow within a collaborative environment. The candidate should be intellectually curious, detail-oriented, and able to balance multiple projects simultaneously, while contributing to the development of tools, models, and insights that drive better decision-making. Candidates with demonstrable prior machine learning experience - including applied ML in industry or research (e.g., NLP, ranking, forecasting, anomaly detection) - are strongly encouraged to apply. Finance experience is a plus but not required. Experience designing and deploying live, distributed systems to disseminate data-driven insights is also highly valued.

  • Build and maintain models that assess performance and liquidity metrics (e.g., NAV analysis, cash flow forecasting, scenario modeling) to inform portfolio management
  • Design, train, and validate ML models (e.g., classification/ranking, time-series forecasting, NLP/embedding-based similarity) to support diligence, portfolio analytics, pricing/matching, and risk identification
  • Productionize and monitor analytics/ML workflows (feature engineering, evaluation, drift checks), emphasizing reproducibility and clear documentation
  • Design, implement, and operate services that expose analytics/ML outputs - such as RESTful APIs and microservices - for use by internal deal teams and clients; ensure reliability, security, versioning, and low-latency responses
  • Develop and present innovative data visualizations, dashboards, and reports that highlight key trends, risks, and insights to senior team members and clients
  • Collaborate with PCA's data team to ensure data-driven insights are incorporated into deal execution and client materials
  • Contribute to internal knowledge-building by researching and applying emerging data science techniques relevant to secondaries analytics
  • Strong proficiency in Python, C++ or Rust; ability to write clean, well-tested, reusable code
  • Experience in applied analytics and ML model development is a strong plus
  • Familiarity with machine learning methods (e.g., forecasting, classification, NLP) and related libraries
  • Minimum 2-3 years of analytics, data science, or banking experience
  • Bachelor's degree in a quantitative field (e.g., Computer Science, Statistics, Engineering, or related)
  • Experience developing and operating production-grade RESTful APIs/microservices (e.g., FastAPI/Flask)
  • Containerization (Docker), orchestration/serverless (Kubernetes, Azure Functions/App Service)
  • Messaging/streaming (Kafka/Event Hubs), caching (Redis), CI/CD, and observability (logging, metrics, tracing)
  • Intellectual curiosity about AI's role in reshaping financial services and practical interest in experimenting with new tools
  • Strong verbal communication skills, able to explain technical work clearly to non-technical audiences, including senior bankers
  • Organizational skills and the ability to manage multiple high-impact projects with guidance
  • Medical, prescription, dental, and vision insurance, including healthcare savings and reimbursements accounts
  • 401(k) Retirement Plan
  • Life and disability insurance, including additional voluntary financial protection insurance
  • Well-being resources and programs, including mental health and mindfulness programs, digital wellness platforms, well-being events, and targeted on-site health services
  • Family-building and family-support benefits
  • Paid parental, caregiver, marriage and bereavement leave
  • Commuter benefits, health club membership discounts, and other corporate discounts
  • Paid holidays, vacation days, personal days, sick days, and volunteer opportunities
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