Working for Trunk Club

When you join Trunk Club, you join the Nordstrom family. Our fast-paced and entrepreneurial environment is paired with the strong history and experience of a retail legacy. We have access to some of the greatest minds in retail and technology and are constantly creating innovative strategies to develop the ultimate apparel solutions. We welcome your adaptability, your curiosity, and your passion to contribute to our unparalleled shopping experience!

Who we are

At Trunk Club, we develop machine learning algorithms that enable the business to make data-driven decisions, from whom marketing targets for re-engagement credits, to which merchandise to recommend for a given customer. Our data scientists dive into readily accessible data and tools thanks to our diligent data engineering team. Our stack provides data scientists the capability to easily turn an algorithm into an API, and run follow-up A/B tests using a range of multivariate models at your disposal. Every team relies not only on the data insights collected, but more importantly in the clever ways that we present it at every step in our experience. 

Data Science helps drive Trunk Club. Every member plays a critical role in influencing the company on the best ways to grow and change. You will have autonomy to collaborate with every team and be directly connected to decision makers without bureaucracy.

Who you are

• A self-starter. You love what you do and are motivated to find the next improvement opportunity.
• A learner. You have an insatiable thirst for knowledge and greater understanding.
• A conversationalist. You speak the language of statistics, and you can communicate with technical and non-technical users alike.
• An innovator. You're interested in the "why" and the solutions that make things more interesting and efficient.

What you'll do

• Build Machine Learning models that power our apps and inventory classification. Our preferred language is currently Python.
• Research and develop predictive algorithms using various supervised and unsupervised statistical concepts, such as time series, multivariate methods, GLM, and Bayesian inference.
• Continue to invest and expand our core skillsets in the areas of big data machine learning techniques, such as gradient boosting, bagging, recommender systems, and NLP.
• Collaborate with internal and external stakeholders to identify business opportunities, and how to translate the opportunities into actionable analytical solutions.
• Work with technology partners to test and implement solutions.
• Communicate and present algorithm solution and outcome with other teams through data visualization.

What your background may look like

• MS in a quantitative field from a top ranking program, PhD is preferred.
• 3+ years of relevant industry experience (post academia).
• Proficiency with Python, Jupyter, and Spark is preferred. Will also consider strong quantitative candidates with background in R or other programming languages.
• Experience with working in an agile team environment
• Experience with communicating and presentation highly quantitative concepts to a non-quant audience.

How we work

• With open minds. We are committed to building a diverse team of people with unique perspectives. This encourages a healthy and inclusive environment that builds a more sustainable, successful company.
• With others. We collaborate cross-functionally to solve problems and deliver the best products for our customers.
• With transparency. We have an open, collaborative team environment. No cubicles, no private offices.
• With agility. We don’t believe in following a process for process’s sake. We ship frequently and focus on delivering incremental value.
• With pride. We value our people most of all. We invest in ourselves by applying our own strengths and interests to company needs.

A few of our perks

• Lunch and learns
• Annual stipend for continuous education
• Tech all-hands every other Friday
• Hack days
• Team outings
• Nordstrom discount
• Flexible work environment
• Social environment with built-in bars