Vice President or Principal, Investment Strategy & Risk Management

Adams Street Partners•Chicago, IL

23h•$175,000 - $250,000

About The Position

Adams Street Partners is a global private markets investment manager with nearly $73 billion in assets under management. The firm is 100% employee-owned, fostering a unique culture of collaboration, intellectual rigor, integrity, and professional development. As a private markets pioneer, Adams Street has been serving leading global clients for over 50 years. The Investment Strategy and Risk Management (ISRM) team plays a crucial role in the firm's top-down portfolio construction and ensures client portfolios align with investment recommendations. This is a highly visible position with interaction across Senior Management and client-facing teams.

Requirements

Advanced degree in Mathematics, Statistics, Computer Science, Finance, Economics, or a similar quantitative field.
5–10 years of relevant experience in a quantitative role within asset management.
Minimum of 2 years of experience involving private markets investment processes and portfolios, such as private equity or private debt.
Strong quantitative, analytical, critical thinking, and problem-solving skills, with the ability to apply robust statistical techniques to large, complex, and imperfect datasets.
Exposure to quantitative or statistical modeling techniques used in portfolio analytics, forecasting, and risk management.
Strong programming capabilities, including proficiency in Python, R, SQL, and/or C++.
Experience with common database and software platforms required.
Ability to translate technical methodologies into clear, commercial, and client-oriented insights.
Demonstrated experience communicating and collaborating across multiple internal and external stakeholders, including technical and non-technical audiences.
Ability to manage priorities independently, maintain accuracy under tight deadlines, and drive projects from concept through execution.

Nice To Haves

CFA® charterholder preferred but not required.
Background in quantitative finance, financial engineering, or quantitative modeling strongly preferred.
Familiarity with machine learning and AI workflows preferred.
Strong understanding of investment management concepts, including accounting principles, portfolio theory, equity valuation, factor models, asset allocation, portfolio optimization, liquidity risk management, and performance measurement.
Familiarity with private investment vehicles and the considerations involved in managing private capital strongly preferred.
Experience directing and managing support staff a plus.

Responsibilities

Design and build statistical models to evaluate alternative datasets, assess portfolio risk, and optimize investment strategies for illiquid assets, including private equity and private debt.
Translate complex private markets data into actionable, client-ready insights for internal stakeholders and external clients.
Integrate, clean, and analyze large and complex datasets, including alternative investment datasets that may be unstructured or imperfect.
Identify value drivers, market behaviors, and trends that can inform investment decision-making.
Develop advanced analytic models, scenario analyses, and simulation-based frameworks, including Monte Carlo simulations, to support risk-aware portfolio construction and investment processes across subclasses, strategies, and products.
Generate original, proprietary research and develop clear, concise white papers, presentations, and other materials for internal stakeholders and external clients.
Partner with software developers, Data Management, IT, and model validation teams to deploy quantitative code and analytics.
Maintain and enhance existing analytic applications and support the use of analytic models for marketing, client service, and investment-related use cases.
Work closely with technical and non-technical stakeholders to develop solutions for ISRM and other internal consumers.
Collaborate with existing technical resources to optimize where data is stored, how it is accessed, and how end users can effectively leverage data and analytics.
Manage multiple workflows and projects, including tracking dependencies, deliverable dates, milestones, and stakeholder inputs.
Prioritize and execute work independently while maintaining accuracy, quality, and timeliness.