About the Company
Boxed is a rapidly growing, e-commerce retailer built; on the foundation of a world-class proprietary technology platform. With 7+ years of evolution, iteration, & successful disruption of the U.S. wholesale club industry, Boxed has developed a comprehensive tap-to-ship E-commerce tech stack few other companies can boast. With Boxed, customers can have their household, pantry, & personal care essentials delivered to their home or office with no membership fee. Our goal is to leverage our technology & data to deliver a superior shopping experience to our customers via our web & mobile app platforms, bringing "family-sized value" right to their doorstep.
Our office is a dynamic, collaborative family of individuals. At our core, we are a data-driven, customer-centric, technology company, & data truly is at the center of everything we do. We are a vibrant, fun & close group of engineers, product managers, data scientists, analysts, & operations specialists with a passion for driving superior value & experience to our customers.
About the Role - Senior Data Scientist
As part of the Data Science team, you will work alongside product managers, engineers & business stakeholders to build data products using machine learning. The tools we use most are Python, UNIX & SQL.
The ideal candidate is driven by curiosity, passionate about creative problem solving, & thrives in an environment where learning & resourcefulness are key. You'll need an entrepreneurial mindset, & you need to nimble & scrappy ("Hey, we're still a start-up!!).
Your strong ML & engineering fundamentals will give you the hard skills necessary to build scalable solutions, & your ability to understand our business & collaborate effectively within & across teams will help to maximize the value you can bring.
The role will report to the VP of Data Science.
- gain a deep understanding of Boxeds business & its organization
- see things from the customers perspective, & appreciate the roles of personalization & basket building in the customer experience
- develop, QA & maintain predictive machine learning models to address business problems
- apply techniques like classification, regression, causal inference, Bayesian statistics & neural networks
- find ways to apply new developments in ML to practical problems
- uncover new problems to solve that will impact our business
- Investigate model performance & determine when refits are needed
- Ensure projects are completed on time & with a high degree of accuracy
- Ensure all models are following the established rules for data privacy & governance of production models
- Stay up-to-date on the latest developments in machine learning & AI
- 3-5 years experience building machine learning models in a practical setting; experience in an e-commerce, SaaS and/or growth setting definitely a plus
- BS/BA degree in a quantitative field preferred
- ability to understand & write idiomatic UNIX shell scripts, SQL & Python code, including Python Standard Library & other common libraries for data analysis.
- strong communications skills & the ability to target a presentation to its audience
Benefits & Perks
- Great work environment
- Working with driven, intellectually voracious & generally awesome people
- Competitive salary
- Stock options
- Unlimited vacation
- Full healthcare benefits