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Rent The Runway // designer dresses & accessories rental
 
Engineering, Full Time    Brooklyn, NY (Rent the Runway HQ)    Posted: Saturday, September 25, 2021
 
   
 
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JOB DETAILS
 

About Us:

Rent the Runway (RTR) is transforming the way we get dressed by pioneering the worlds first Closet in the Cloud. Founded in 2009, RTR has disrupted the $2.4 trillion fashion industry by inspiring women with a more joyful, sustainable & financially-savvy way to feel their best every day. As the ultimate destination for circular fashion, the brand now offers infinite points of access to its shared closet via a fully customizable subscription to fashion, one-time rental or ownership. RTR offers designer apparel, accessories & home decor from 700+ brand partners & has built in-house proprietary technology & a one-of-a-kind reverse logistics operation. Under CEO & Co-Founder Jennifer Hymans leadership, RTR has been named to CNBCs Disruptor 50 five times in ten years, & has been placed on Fast Companys Most Innovative Companies list multiple times, while Hyman herself has been named to the TIME 100 most influential people in the world & as one of People magazines Women Changing the World.

About the Team: 

Data is core to our growing business & has been ingrained in the company's DNA since its founding. The Data Science team is the engine that powers our data-driven culture. We extract meaning from RTRs many, rich customer interactions & partner with decision makers across the company to turn insights into actions. Our team of well-rounded data scientists manages data models, defines & analyzes performance metrics, builds reporting, runs A/B experiments, & develops statistical & machine learning models.

About the Job:

Inventory is the largest asset on Rent the Runways balance sheet & among our most important competitive differentiators. We collect & codify a tremendous amount of information on the inventory we buy & how our customers use it. We are looking for a Data Scientist on our Inventory Analytics team to put this data to use, helping us bring more science to the art of fashion. In this role, you will partner with planners, buyers, & site merchandisers on the fashion team to bring analytical frameworks & statistical models to elusive inventory problems, such as inventory longevity, demand forecasting, pricing, network effects, & much more. Our unique business model - inclusive of subscription, rental, & resale - provides for a steady stream of novel problems. You will identify clever adaptations of solutions from other industries & flex your creative muscles to drive serious business impact!

What Youll Do:

  • Identify new opportunities to leverage data science (in areas such as pricing, demand forecasting, inventory longevity, & profit modeling) that improve buying & operational decisions
  • Work with & develop ML models, perform A/B testing, & apply quantitative analysis & data mining techniques
  • Determine & calculate KPIs to objectively evaluate inventory health & performance
  • Contribute to our inventory data model, creating new reusable tables with built-in data validations & extensible architecture
  • Build data tools & dashboards that empower various stakeholders throughout the organization

About You:

  • You have a strong quantitative and/or technical academic background, such as Mathematics, Computer Science, Statistics, Economics, Finance, or Physics (masters is a plus!)
  • You have 3+ years experience in a data analytics and/or data science role, using quantitative analysis to solve challenging, real-world problems (background in e-commerce, supply chain, finance, or pricing is a plus)
  • You have hands-on experience developing statistical models in Python and/or R
  • You have a strong handle on SQL; you can comfortably navigate joins, subqueries, window functions, & common table expressions
  • You have experience creating dashboards with a BI tool such as Tableau or Looker
  • You have a track record of building strong relationships with cross-functional partners
  • Youre able to communicate effectively with a wide-range of audiences
  • Youre able to quickly learn new tools & data analysis methods
  • You have a passion for data & its fundamental ability to create value
  • Youre extremely curious & excited to dive into complex problems

Benefits:

At Rent the Runway, were committed to the wellbeing of our employees, & aim to create a workplace that fosters both personal & professional growth. Our inclusive benefits include, but are not limited to:

  • Paid Time Off including vacation, paid bereavement, & family sick leave - every employee needs time to take care of themselves & their family.
  • Universal Paid Parental Leave for both parents + flexible return to work program - because we know your newest family member(s) deserve your undivided attention.
  • Paid Sabbatical after 5 years of continuous service - Unplug, recharge, & have some fun!
  • Exclusive employee subscription & rental discounts - to ensure you experience the magic of renting the runway (and give us valued feedback!).
  • Comprehensive health, vision, dental, FSA & dependent care from day 1 of employment - Your health comes first & weve got you covered.
  • 401k match - an investment in your future.
  • Company wide events & outings - our team spirit is no joke - we know how to have fun!
  • Flexibility Policy - when our corporate employees return to the office post COVID they will have the option to work remotely 2-3 days a week.

Rent the Runway is an equal opportunity employer. In accordance with applicable law, we prohibit discrimination against any applicant or employee based on any legally-recognized basis, including, but not limited to: race, color, religion, sex (including pregnancy, lactation, childbirth or related medical conditions), sexual orientation, gender identity, age (40 & over), national origin or ancestry, citizenship status, physical or mental disability, genetic information (including testing & characteristics), veteran status, uniformed servicemember status or any other status protected by federal, state or local law.

 
 
 
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