At Everlane, we want the right choice to be as easy as putting on a great T-shirt. That’s why we partner with ethical factories around the world. Work with high quality and more sustainably sourced materials. And share the true cost of every product we make. But there's a lot more work to be done, and we're excited to be growing a team of motivated humans that are up for the challenge.
The data team at Everlane is tasked with enabling the company to use data to make decisions and improve our product, tackling problems spanning operations, marketing, product, and ecommerce. Our data scientists lean on a full-stack set of methodologies and tools to solve these problems, taking an initial open ended question to the eventual business implementation of a model.
We’re looking for a Data Scientist to build data products addressing some of our toughest problems in the demand planning and logistics domains. You’ll be combining strong modeling and inference skills, along with a deep understanding of the business to deliver decision making systems that allow us to scale the backbone of the company. This role has a high level of ownership- we really want someone who is not afraid to think big, while also having the pragmatic toolkit to efficiently ship impactful data models.
- Partner with the business to flesh out the parameters and goals of data science problems
- Use data analysis to answer questions around demand patterns, supply chain efficiency, and return rate tendencies
- Design experiments (both natural and RCTs), and study their results to identify important causal levers within the company
- Develop and productionize forecasting models that allow us to better predict future demand at varying dimensions and levels
- Create robust optimization frameworks, thinking through the right tradeoffs and rewards for transportation, fulfillment, and physical retail
- Build the scaffolding to support the maintenance of deployed models, such as automated diagnostics, quality checks, etc.
We'd love to hear from you if you have:
- BA/BS in a quantitative field -- MS or PhD preferred
- 4+ years experience as a data scientist in industry solving operational problems
- 2+ years specific experience in forecasting, operations research, and/or optimization
- Track record of shipping data products: being able to write production level data science code while also conceptually understanding tradeoffs in production systems
- Strong understanding of statistics and predictive modeling
- Expertise in SQL and querying databases in order to perform analysis and build predictive models
- Expertise in a computing language (R/Python), including strong data toolkit within your respective language (we’re interested in hearing about your “bread and butter”, whether it’s tidyverse + ggplot2, or pandas + seaborn, etc.)
- Comfort in a cloud computing environment (we’re an AWS shop) and/or navigating a command line based environment