Quantitative Researcher for Finance

Wealthfront is the only robo-advisor to offer both investment management and financial planning exclusively through software. Because of this approach, we've quickly become the automated advisor of choice among young people. Anyone can open a Wealthfront investment account with $500 to access a unique Passive+ investment strategy that includes a combination of a diversified portfolio of ETFs and tax minimization strategies.

We are seeking Quantitative Researchers to join the Research team at Wealthfront. The primary responsibility of the role is to investigate and develop proprietary, automated investment strategies addressing our clients' various investment problems. Your focus will span topics related to asset allocation, portfolio construction (taxable and non-taxable), investment vehicle selection, tax efficiency, optimization, trade execution, behavioral finance, as well as, risk modeling and risk tolerance assessment. Successful candidates will combine an ability to derive and apply quantitative models to the empirical analysis of financial and client data. Code and models are the way we express insights and analysis, thus you need to be comfortable working with large datasets and writing significant amounts of R code.

• 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