Senior Data Scientist
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 models that enable the business to make data-driven decisions, from whom marketing targets for re-engagement credits to which merchandise should be shoppable for a given customer. Our stack makes it easy and painless to 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 we collect, but more importantly in the clever ways that present it to every in our experience.
Data Science helps drive Trunk Club. Every member helps inform 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.
What You'll Do
- Developing and maintaining Machine Learning infrastructure that powers our ranking models, member apps, inventory classification, etc. Our preferred language is Python and you'll regularly be working with real-time information from Kafka streaming systems.
- Researching, developing, and implementing predictive algorithms using various regression techniques, deploying them as real-time APIs in our micro-service infrastructure.
- Utilizing Natural Language Processing to understand text content across products, including reviews and interactions between users, stylists, and products.
- Using Computer Vision (OpenCV) for image content analysis of novel and existing clothing items: classification, quality, attractiveness, similarity, extraction of features for ranking models.
- Identifying suspicious transactions and malicious users for Fraud. Can you beat SaaS fraud platforms? We’re betting so.
- Determining the optimal inventory levels to help us effectively manage inventory needs while meeting revenue goals.
- Using a range of clustering techniques to identify latent clusters of customers based on purchases, demographics, styles, etc.
- Brainstorming new tools to help minimize the risk of experimenting with new algorithms.
What Your Background May Look Like
- Graduate degree in quantitative discipline with 2-3 years of relevant industry experience
- Experience building and deploying Machine Learning models, and providing vision within a team environment.
- Strong programming ability in Python with Jupyter, Pandas, and sklearn.
- Proven track record working hands-on with data end-to-end.
- Demonstrated success visualizing data and explaining complex concepts through expressive communication.
Who You Are
- An evangelist. You love what you do and have a knack for communicating technical jargon to any audience.
- A learner. You have an insatiable thirst for knowledge and greater understanding.
- A pragmatist. Your goal is to create useful products, not build technology for technology’s sake.
- An entrepreneur. You’re truly invested in the success of the business.
How We Work
- With others. We collaborate cross-functionally to solve problems and deliver the best products for our customers.
- With transparency. We have an open team room. 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 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 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 lunches every other Friday
- Hack days
- Team outings
- Nordstrom discount
- Flexible work environment
- Social environment with built-in bars