Quantitative Researcher, Evergreen Portfolio Management (Boston or Toronto)

Résumé du poste

Job Description Summary For over forty years, HarbourVest has been home to a committed team of professionals with an entrepreneurial spirit and a desire to deliver impactful solutions to our clients and investing partners. As our global firm grows, we continue to add individuals who seek a collaborative, open-door culture that values diversity and innovative thinking. In our collegial environment that’s marked by low turnover and high energy, you’ll be inspired to grow and thrive. Here, you will be encouraged to build on your strengths and acquire new skills and experiences. We are committed…

Détails du poste

Job Description Summary For over forty years, HarbourVest has been home to a committed team of professionals with an entrepreneurial spirit and a desire to deliver impactful solutions to our clients and investing partners. As our global firm grows, we continue to add individuals who seek a collaborative, open-door culture that values diversity and innovative thinking. In our collegial environment that’s marked by low turnover and high energy, you’ll be inspired to grow and thrive. Here, you will be encouraged to build on your strengths and acquire new skills and experiences. We are committed to fostering an environment of inclusion that promotes mutual respect among all employees. Understanding and valuing these differences optimizes the potential of both the individual and the firm. HarbourVest is an equal opportunity employer. This position will be a hybrid work arrangement. You will receive 18 remote workdays per quarter to use at your discretion, subject to manager approval. For example, you may choose to work in the office 4 days per week and take one remote day weekly (typically 13 weeks per quarter), leaving 5 additional remote days to be used as needed. As a member of the Quantitative Investment Sciences (QIS) team, this quantitative researcher will work with a team of experienced researchers to develop quantitative modeling and analysis for management of private equity evergreen portfolios. This motivated individual will be dedicated to supporting and collaborating with HarbourVest’s Evergreen fund team on pipeline monitoring, liquidity management, portfolio construction, and stress testing while generating quantitative insights for client engagements and fundraising. Projects will involve leveraging large proprietary private market datasets and statistical models to systematize and enhance portfolio management decision making for these sophisticated fund structures. This is an opportunity to join a highly diverse and growing team passionate about pioneering the application of quantitative research, ML/AI and data science to private markets investing and risk management. The ideal candidate is someone with: Passion for financial markets and investing, quantitative research with complex datasets, and demonstrated intellectual curiosity. Innovative and entrepreneurial attitude. Comfortable taking initiative. Excels at clearly and effectively communicating quantitative insights. Strives in a collegial and collaborative team-oriented environment. Results and detail oriented. Willing to work in a position with uneven and high priority project work. What you will do: Conducting quantitative modeling and analysis to support management of evergreen private equity portfolios (80%) You will play a lead role in leveraging proprietary private markets datasets and models to characterize market risk/return relationships, explore liquidity and market stress events, and develop strategies to optimize liquidity management and fund performance. Accountable for communicating analysis results and actionable insights to the Evergreen fund team. Support and drive adoption and integration of quantitative models to enhance portfolio construction and management processes. Responding to ad-hoc quantitative analysis requests (20%) Supporting client facing teams in conducting ad-hoc analysis and responding to client requests. What you bring: Experience in the financial services industry in a quantitative role is required; however, prior private markets experience is not required. Demonstrate rigorous statistical analysis and experience analyzing large datasets. Strong Python programming skills (including numerical, statistical modeling and visualization libraries) with SQL experience is required. Prior experience in Monte-Carlo simulation methods is preferred Ability to learn and enhance an existing code base is required Prefer prior independent research experience in academia or industry Education: Bachelor of Arts (B.A) or Bachelor of Science (B.S.) required Prefer master's degree or Ph.D. in a technical field Experience: 3+ years of experience in a quantitative finance role #LI-Hybrid Base Salary Range $210,000.00 - $280,000.00 This USD base salary range represents only one component of total compensation for this role and is provided in accordance with local requirements. This role is eligible for a discretionary annual bonus, which is determined based on individual and overall firm performance. In addition to salary and bonus, total compensation may include eligibility for long-term reward programs and a comprehensive total rewards package that may include retirement, health, insurance, paid time off, and wellness programs. Our total rewards offerings are influenced by several business factors, and eligibility for certain components will vary by position and geography. Please note the posted ranges do not apply outside the U.S. and should not be converted to other currencies as a proxy for compensation in other countries. HarbourVest is an independent, global private markets firm with over 43 years of experience and more than $146 billion of assets under management as of June 30, 2025. Our interwoven platform provides clients access to global primary funds, secondary transactions, direct co-investments, real assets and infrastructure, and private credit. Our strengths extend across strategies, enabled by our team of more than 1,270 employees, including more than 230 investment professionals across Asia, Europe, and the Americas. Across our private markets platform, our team has committed more than $64 billion to newly-formed funds, completed over $66 billion in secondary purchases, and invested over $49 billion in direct operating companies. We partner strategically and plan our offerings innovatively to provide our clients with access, insight, and global opportunities.

Ce que vous ferez

The role involves conducting quantitative modeling and analysis to support the management of evergreen private equity portfolios, focusing on characterizing market risk/return relationships and optimizing liquidity management. A key part of the responsibility includes leveraging proprietary datasets and models to enhance portfolio construction and responding to ad-hoc quantitative analysis requests for client-facing teams.

Exigences

Candidates must have experience in a quantitative role within the financial services industry, demonstrating rigorous statistical analysis and experience with large datasets, along with strong Python programming skills and SQL experience. A Bachelor's degree is required, though a Master's or Ph.D. in a technical field is preferred, along with 3+ years of quantitative finance experience.

Avantages

• Discretionary annual bonus • Long-term reward programs • Retirement • Health • Insurance • Paid time off • Wellness programs

Compétences indiquées

• Dedicated · Souhaitée
• SQL · Souhaitée
• collaborative · Souhaitée
• Technical · Souhaitée
• analysis · Souhaitée
• Health · Souhaitée
• Client · Souhaitée
• Energy · Souhaitée
• management · Souhaitée
• Decision Making · Souhaitée
• Time · Souhaitée
• Python · Souhaitée

Autres compétences pertinentes

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• Quantitative Modeling
• Statistical Analysis
• Python Programming
• SQL
• Monte-Carlo Simulation
• Data Visualization
• Liquidity Management
• Portfolio Construction
• Stress Testing
• Private Equity
• Machine Learning
• Artificial Intelligence
• Data Science
• Risk Management
• Communication