Quantitative Risk Manager
Founded in 2014, Opendoor’s mission is to empower everyone with the freedom to move. We believe the traditional real estate process is broken and our goal is simple: build a digital, end-to-end customer experience that makes buying and selling a home simple, certain and fast. We have assembled a dedicated team with diverse backgrounds to support more than 100,000 homes bought and sold with us and the customers who have selected Opendoor as a trusted partner in handling one of their largest financial transactions. But the work is far from over as we continue to grow in new markets. Transforming the real estate industry takes tenacity and dedication. It takes problem solvers and builders. It takes a tight knit community of teammates doing the best work of their lives, pushing one another to transform a complicated process into a simple one. So where do you fit in? Whether you’re passionate about real estate, people, numbers, words, code, or strategy -- we have a place for you. Real estate is broken. Come help us fix it.
About the Team:
Opendoor, a leading tech-driven real estate platform, is seeking a Risk Quant to join the Risk Management team. We are looking for a candidate who can bring a unique blend of skills in creating data-driven insights, market and business modeling and Python-based algorithm development.
Role Responsibilities:
- Develop and refine quantitative models to assess various types of risks, including market, operational and product risks for Opendoor’s businesses.
- Leverage market and operational data to derive insights from market trends, economic indicators, and internal data sets. Present findings to stakeholders to inform strategic decisions, and create systems and processes that produce structured decision-making.
- Work closely with cross-functional teams, including finance, data science, and operations, to align risk management strategies with company objectives. Prepare and present regular risk reports to management and stakeholders.
- Stay abreast of the latest research and methodologies and continually refine and advance our risk management strategies.
Skills Needed:
- Master’s degree in Finance, Economics, Statistics, or a related quantitative field.
- Proven experience in developing Python-based algorithms for complex financial models.
- Excellent verbal and written communication skills, with the ability to explain complex concepts to non-technical stakeholders.
- Strong understanding of market dynamics. Real estate market experience is a plus.
- Ability to translate theoretical models into practical, actionable strategies.
- Excellent problem-solving skills and the ability to work in a fast-paced, evolving environment.
Bonus Points, if:
- CFA Designation
- GARP FRM Accreditation
- Professional experience with CVXPy
Location:
Remote roles in the US are available in all states EXCEPT Hawaii, Alaska, Montana, or any US Territories. Strong preference for San Francisco or New York City.
Compensation:
Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The pay range for most locations in the US is $124,000 - $192,500 annually. In the SF Bay Area of California, Seattle, and New York City Metro area the base salary range is $155,200 - $213,400. Pay within the range varies by work location and may also depend on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process. We also offer a comprehensive package of benefits including paid time off, 12 paid holidays per year, medical/dental/vision insurance, basic life insurance, and 401(k) to eligible employees.
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