About us:

Trunk Club was started to solve a simple problem – shopping for clothes in stores or online just doesn’t work for most people. It’s overwhelming, inconvenient, and takes way too much time. With Trunk Club, people can discover awesome clothes that are perfect for them without ever having to go shopping. We combine top brands, expert service, and unparalleled convenience to deliver a highly personalized experience that helps people look their best and save them time.

Our team is based in Chicago, IL and has grown from four to over 900 since starting out in December 2009. We're actively looking for amazing people to join our team.

Why is Data Science important at Trunk Club?

For a data scientist, Trunk Club is a retail dream. We have rich feedback, profile, and sizing information for all of our customers and as a data scientist you have the ability to directly influence every facet of our experience.

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 everyone 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 type of work will the Sr. Data Scientist perform?

• Partner with our software engineers to architect and develop 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.
• Research, develop, and implement predictive algorithms using various regression techniques, deploying them as real-time APIs in our micro-service infrastructure.
• Work directly on any number of critical business challenges, such as:
• Utilize Natural Language Processing to understand text content across products, including reviews and interactions between users, stylists, and products.
• Use 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.
• Use a range of clustering techniques to identify latent clusters of customers based on purchases, demographics, styles, etc.
• Support less experienced team members, advising them on challenges like defining problems, choosing techniques, evaluating results, and launching models.
• Use your experience to help us build a high-performing data science team; assist in overcoming process and cultural challenges, hiring top data science talent, and building skunkworks tools that speed development and minimize our risk of experimenting with new algorithms.

We care about the following qualifications:

• 3+ years of industry experience building and productionizing machine learning systems from initial analysis to product and actionable insight.
• Ability to explain underlying mathematics of machine learning systems.
• Strong programming ability (Python, consideration given for R). Our team is responsible for delivering actionable insights and enabling data driven decisions. Candidate must be able to build out an API driven by classical statistics or machine learning when applicable.
• Knowledge of Bayesian probability and application of Bayesian methodology to common data science problems.
• Previous experience with experimental design (Previous research experience is a plus). Knowledge of when to use the most appropriate analysis (e.g., ANOVA vs. multi-level modeling) and common problems with data sets (e.g., heterogeneity and unbalanced designs).
• Strong SQL experience. We interact with the BI and Data Warehouse team using MS SQL Server, Postgres, and Redshift. Candidate must be able to explain complex joins and sub-queries if asked and explore a database on the fly.
• Strong presentation and communication skills. Our insights drive the business and without the ability to explain those insights accurately but without jargon, we fail. Previous experience presenting or lecturing to large groups is a plus.
• Ability to operate semi-autonomously to accomplish various business needs before a given deadline. You are given lateral movement and must use that time wisely.
• Highly agreeable and able to take constructive criticism well.
• Master’s in quantitative discipline or equivalent experience. Ph.D. preferred.