ROLE:
Point72 Asset Management is seeking a mid-level Quantitative Risk Analyst to join its Risk & Quantitative Research team.
The RQR team plays a vital role in the Firm’s investment process, building a deeply rooted culture of efficient risk management and factful performance attribution. Quantitative Risk Analysts perform research to identify opportunities for improved risk management, investment behavior, and portfolio construction, with the goal of helping the firm deliver superior risk-adjusted performance. The paramount mission of the team is to protect the Firm from improper levels of exposure and ensure that risk-taking is always efficient and deliberate.
The ideal candidate is an intelligent and creative problem solver who can articulate one’s ideas effectively to a diverse audience in a fast-paced environment. Experience in quantitative investment research is a plus. At this moment, we are specifically looking for a candidate who is well-versed in rates.
THE QUANTITATIVE RISK ANALYST WILL:
- Analyze portfolios and strategies to identify the risk and performance drivers; expand the current risk infrastructure to facilitate efficient risk management as well as improve understanding of portfolio construction and investment behavior.
- Work with senior risk managers to engage with portfolio managers and research analysts on topics such as risk limit usage, portfolio construction, tail exposure, and forward-looking risk events and address ad hoc inquiries from senior management, PMs, and risk managers.
- Help design and improve stress testing, Value at Risk, and various limit frameworks for macro portfolios.
- Conduct research to develop innovative risk management approaches, tools, and analytics that can be used by investment teams and risk managers, to achieve better comprehension of portfolio risk characteristics and deliver those research findings to senior management.
- Partner with the technology team to convert prototypes into production and continuously enhance them as necessary and collaborate with macro strategists and the valuation team to ensure the high quality of valuation and risk models.
WE SEEK CANDIDATES WITH:
- Master’s degree or higher in quantitative finance, statistics, math, engineering, or computer science.
- 3+ years of work experience in a quantitative research, trading, or risk management capacity related to macro products (rates and/or FX).
- Solid product knowledge and analytical rigor in terms of pricing models, risk sensitivities and the best practice for risk aggregation in a portfolio context.
- High level of proficiency in SQL and quantitative programming (Python, MATLAB, R) and experience dealing with large data sets.
- Strong attention to detail and willingness to go the extra mile to ensure the accuracy and quality of the work.
- Excellent communication skills and prior experience interacting with portfolio managers.
- Ability to manage multiple tasks and deadlines independently in a fast-paced environment.
- Ability to proactively seek new ideas and solution to improve the status quo.
- Strong work ethic; reliable and accountable.
- Ability to work cooperatively with all levels of staff as part of a team.
- A commitment to the highest ethical standards and to act with professionalism and integrity.
POINT72 OFFERS SUBSTANTIAL CAREER OPPORTUNITIES:
- We are a workplace where performance and integrity go hand in hand
- We are committed to personal and professional development
- We expect and reward innovation and creativity
- We create opportunities for long-term careers
- We measure success by the merits of the work, its quality and the results obtained
Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its investors through fundamental and systematic investing strategies across asset classes and geographies. We aim to attract and retain the industry’s brightest talent by cultivating an investor-led culture and committing to our people’s long-term growth.