At Wealthfront we have an ambitious vision to optimize and automate all your personal finances. By delivering our service exclusively through software, we can also offer very low fees and account minimums. Over the past six years our clients have rewarded us with $10 billion to manage and we have attracted some of the best venture capital firms in the business including Benchmark Capital, Greylock, Index Ventures and Social Capital. We recently closed a $75 million round of funding from Tiger Global and are rapidly growing our team. So if youre passionate about helping people secure their ambitions while helping to change an industry, keep reading.
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