Associate, Quantitative Research Group, GCS

Over the last 20 years, Ares’ success has been driven by our people and our culture. Today, our team is guided by our core values – Collaborative, Responsible, Entrepreneurial, Self-Aware, Trustworthy – and our purpose to be a catalyst for shared prosperity and a better future. Through our recruitment, career development and employee-focused programming, we are committed to fostering a welcoming and inclusive work environment where high-performance talent of diverse backgrounds, experiences, and perspectives can build careers within this exciting and growing industry.

Job Description

Ares Management Corporation (NYSE: ARES) is a leading global alternative investment manager offering clients complementary primary and secondary investment solutions across the credit, private equity, real estate and infrastructure asset classes. We seek to provide flexible capital to support businesses and create value for our stakeholders and within our communities. By collaborating across our investment groups, we aim to generate consistent and attractive investment returns throughout market cycles. As of December 31, 2021, Ares Management Corporation's global platform had approximately $306 billion of assets under management, with approximately 2,100 employees operating across North America, Europe, Asia Pacific and the Middle East. For more information, please visit www.aresmgmt.com.

The Ares Quantitative Research Group (QRG) is a pioneer in the application of quantitative analytics to private markets and is the central hub of Ares IQ, the overarching brand for Ares’ quantitative analytic capabilities. QRG works across asset classes – credit, private equity, private real estate, and infrastructure – to provide investible insights to Ares’ investment teams, to deepen relationships with Ares’ investors, and to help develop new products for the firm. The group is a leader in private market performance measurement, having played a key role in the development of the Direct Alpha and Excess Value measures. It regularly deals with questions that are novel, benefiting from the opportunities created by the under-researched nature of private assets. QRG consists of two teams, Research and Software, and works closely together with “Ares IQ” quants, who are embedded within Ares investment teams.

Primary functions & responsibilities

• Work with mathematical and statistical models to solve important problems in private market investing, including identifying return drivers and attributes of private market portfolios

• Participate in and eventually lead original research to answer novel questions and produce investible information across private market asset classes

• Help to evaluate clients’ private market portfolios, identifying opportunities for active management in order to achieve portfolio objectives

• Design presentations for internal investment groups, external investors, and conferences

• Contribute to the design, development, and evaluation of proprietary software tools used in the assessment of private market investment opportunities

• Work closely with internal and external clients and, with time, gain exposure to the institutional investor community

Qualifications

Experience Required:

Candidates for an Associate role should have 4+ years of post-undergraduate work or academic experience in a relevant field.

General Requirements:

• Background in quantitative finance, statistics, or a related field.

• Strong writing, communication, and presentation skills. Ares' quants get significant 'air time' and should be comfortable speaking in front of audiences.

• Ability to work both independently and as a productive member of dynamic teams.

• Knowledge of private market performance metrics, valuation methodologies, and frameworks. Alternatively, similar knowledge of public markets and a serious interest in private markets.

• Familiarity with a variety of asset classes, including equity, credit, and real assets

• Demonstrated experience using Python to solve research problems, or experience with R/Stata/MatLab and a willingness to learn Python.

• Experience using statistical models for inferential or causal modeling.

• Experience with predictive modeling techniques, including artificial intelligence and/or machine learning, is a bonus.

• Eagerness to learn and apply novel techniques from academic and practitioner literature.

Reporting Relationships

Compensation

$0.00 - $0.00

There is no set deadline to apply for this job opportunity. Applications will be accepted on an ongoing basis until the search is no longer active.