Quantitative Researcher, Finance
Wealthfront, Redwood City, CA
Plan your future and invest your money with an automated advisor
- Develop portfolio optimization models and investment algorithms
- Build reproducible backtests for proposed models / algorithms
- Conduct empirical statistical analysis / modeling on relevant data and develop actionable insights
- Contribute to the development of research infrastructure for modelling, optimization, backtesting, analytics, and data management, to ensure an efficient and robust research process
- Investigate, identify, and acquire internal / external datasets
- Collaborate with other teams (engineering, product, design, marketing, and compliance) to commercialize new products and ongoing enhancements to existing products
- Masters or PhD degree in finance / economics. Candidates from related disciplines with a strong focus on quantitative analysis (e.g. operations research, statistics) are also encouraged to apply.
- Experience analyzing complex data and building statistical models
- Strong background in econometrics / statistics; experience with optimization desired
- Programming competency in R and / or Matlab and / or Python
- Programming competency in SQL preferred
- Strong presentation skills and ability to communicate technical content to an audience with varied backgrounds
Our mission at Wealthfront is pretty simple: we believe that everyone deserves access to sophisticated financial advice. Over the past five years, Wealthfront has built a technology company focused on re-architecting the finance industry. Some might call us ‘robo-advisor’, but we promise we’re made up of humans. Our world-class research team develops sophisticated and time-tested investment strategies, and our product and engineering teams build the software that enables us to deliver them automatically and at scale, right to your phone.