Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Their mission is to increase the GDP of the internet, and they have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.
What you’ll do
In this role, you will have the opportunity to rethink the sales forecasting pipeline. You’ll evaluate and implement time series models to forecast Stripe’s newest users’ growth, create a framework for outlier detection in the case of unusual growth patterns, and evaluate statistical methods to communicate uncertainty in the forecasts. You’ll also partner with sales in developing new compensation programs using the forecasts and other available data. Finally, you’ll work on building an attribution model to credit sales leads to specific incoming channels (i.e. Outbound, Inside Sales, or Marketing).
- Work closely with the sales team to identify important questions and answer them with data.
- Apply statistical, machine learning 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.
Who you are
Company’s looking for data scientists to join the Data Science team who are excited about applying their analytical skills to understand the users and influence decision making. If you are naturally data curious, excited about deriving insights from data, and motivated by having impact on the business, they want to hear from you.
- 5+ years experience working with and analyzing large data sets to solve problems
- A PhD or MS in a quantitative field (e.g., Economics, Statistics, Engineering, Natural Sciences)
- Expert knowledge of a scientific computing language (such as R or Python) and SQL
- Strong knowledge of statistics, machine learning and experimental design
- Demonstrated track record of identifying, scoping and leading complex data science projects with cross-functional partners and high business impact
- Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner
- Experience working with a sales team
- Prior experience with data-distributed tools (Spark, Hadoop, etc)
- Salary Offer 0 ~ $3000
- Experience Level Junior
- Total Years Experience 0-5
- Dropdown field Option 1