Data ScientistUnited States.

About us

Stockpile is the easiest, fastest way to invest in your favorite companies. It lets users pick a stock and a dollar amount (e.g., $50 of Apple), pay with their debit or credit card, and sign up. Users can also invest in someone’s future with a gift card for stock, or redeem rewards points for stock.

Data Scientist

United States

ABOUT STOCKPILE

Stockpile is the easy and affordable way to buy stock. With Stockpile, you can buy fractional shares of stock in publicly-traded companies. Rather than buying an entire share of stock, you can get just the amount you want. This means you can buy $25 of Amazon stock even though 1 share costs about $1000.

We have also invented the world's first gift card for stock! For the first time ever, you can buy $25, $50, and $100 Stockpile gift cards off the gift card rack at stores like OfficeMax, K-Mart, Safeway, and ToysRUs, or send e-gifts from our website (stockpile.com) or mobile app.

Stockpile's mission is to democratize stock investing. 86% of the population has never had a chance to own stock because it's intimidating and expensive, but it doesn't have to be that way! We've broken down the barriers to stock ownership by building our own fractional shares platform and partnering with Fortune 500 companies to bring the stock market to you, whether you're grocery shopping or doing your mobile banking.

Based in Palo Alto, Stockpile is venture-backed, and our team comes from companies like Facebook, PayPal, and E*Trade. We've been featured in the Wall Street Journal, CNBC, Consumer Reports, and many others. We're building a team of exceptionally talented people to join us on our mission, and would love to talk to you!

WHAT YOU WILL DO

Work closely with product and business teams to identify important questions and answer them with data
Apply statistical and econometric models on large datasets to: i) measure results and outcomes, ii) identify causal impact and attribution, iii) predict future performance of users or products
Design, analyze, and interpret the results of experiments
Drive the collection of new data and the refinement of existing data sources
Write SQL queries to create business analytics and KPI reports
Maintain and improve instrumentation for conversion funnel tracking for major flows.
Build and enhance data warehouse and data visualization pipeline for key product areas
WHAT WE LOOK FOR

3+ years experience working with and analyzing large data sets to solve problems
A PhD or MS in a quantitative field (e.g., Economics, Statistics, Sciences, Engineering, Computer Science)
Expert knowledge of a scientific computing language (such as R or Python) and SQL
Strong knowledge of statistics and experimental design
The ability to communicate results clearly and a focus on driving impact

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