The Wealthfront Data Science Team utilizes our rich financial and behavioral data to influence key product and marketing decisions, as well as to safeguard our clients’ information and assets. The team draws from backgrounds in Computer Science, Natural Sciences, Statistics, Operations Research and Econometrics.
The Data Scientist in this role will be primarily embedded within Wealthfront’s Growth Team. The Growth Team is focused on acquiring new clients, as well as deepening Wealthfront’s relationship to existing clients. The team addresses this mandate by designing creative initiatives that cut across product lines. These initiatives can include testing new in-app features, discovering new channels of client acquisition, launching email campaigns, or targeted incentives – all based on unique insights about our clients and their interaction with the prevailing economic environment.
A fundamental trait for an effective Growth Data Scientist is curiosity for discovering new insights about client behavior. This person will enjoy going deep into the data to understand what’s driving client actions, proposing ideas for new projects and for driving clarity on the ‘why’ behind experiment results.
Technical tools used in this role include Hypothesis testing (potentially with atypical distributions), mathematical transforms of variables, data mining, natural language processing (NLP) and machine learning (ML). You don't need experience in all of the techniques but must have the ability to pick them up as needed.
Potential project areas for this role include (but are not limited to) analyzing client signup flow, creating client groups according to business rules or automated clustering, creating ML models for estimating incentive revenues or costs and Named Entity Recognition using NLP.
Responsibilities
- Demonstrate an owner’s mindset in formulation, execution, communication and timing of your projects.
- Analyze and explain A/B test experiment results. Investigate why the experiment was a success or a failure. Discover client segments for whom the experiment worked unusually well or otherwise.
- Suggest follow ups for recently concluded initiatives and experiments. Create and present rationales for questions including whether the experiment should be continued, and what should be different in the next iteration.
- Work closely with Product, Design, Engineering and User Research members on the Growth Team to craft a long term (quarterly) learning plan and subsequently execute your part in that plan.
- Collaborate with cross functional stakeholders to come up with feasibility of an experiment, experiment structure and opportunity sizing/impact of the experiment to guide the team’s roadmap.
- Work with Data platform teams to procure required (but unavailable) data.
- Enhance overall Data Science team execution through hands-on help, design feedback and peer review.
Requirements
- A Master's or a PhD degree in Computer Science, Statistics, Operations Research, or Natural Sciences with 4+ years of prior experience in a Data Science role. Exceptions to these requirements may be considered on a case-by-case basis.
- Prior experience in Growth or Marketing
- Prior experience analyzing complex experiments, including developing data insights and data backed recommendations for stakeholders.
- Strong communication, storytelling and collaboration skills and a record of partnering across organizations to sharpen project requirements. Sometimes this includes re-framing the original request to solve a more general problem with similar effort.
- Hands-on mathematical and software engineering skills to execute on complex projects.
- Proficiency in Python and SQL.
- Desire and ability to mentor junior Data Scientists within the team by exemplifying math, engineering and technical communication skills.
Estimated annual salary range: $165,000 - $185,000 USD plus equity and a discretionary bonus.
Benefits include medical, vision, dental, 401K plan, generous time off, parental leave, wellness reimbursements, professional development, employee investing discount, and more!
United States
