Quantitative Researcher, Evergreen Portfolio Management (Boston or Toronto)
About The Position
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.
Requirements
- 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.
- Ability to learn and enhance an existing code base is required
- Bachelor of Arts (B.A) or Bachelor of Science (B.S.) required
- 3+ years of experience in a quantitative finance role
Nice To Haves
- Prior experience in Monte-Carlo simulation methods is preferred
- Prefer prior independent research experience in academia or industry
- Prefer master's degree or Ph.D. in a technical field
Responsibilities
- 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.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Number of Employees
1,001-5,000 employees
