Data Scientist

Birchbox is beauty made easy. Founded in 2010, we redefined the way people shop for beauty and grooming by pairing a monthly delivery of personalized samples with original content and a robust e-commerce shop. We partner with the best brands in the industry, from mainstream favorites to niche up-and-comers, and use a proprietary algorithm to send the right products to the right people, based on their profiles and preferences.

The Data Science, Analytics and Insights team is comprised of data scientists, data engineers and statistical analysts aiming to help Birchbox change the way people discover products via deep personalization, smart recommendation, and great data-driven decisions overall. As a data scientist in the team, your projects range across the full spectrum of Machine Learning and Applied Statistics.

• Monthly box personalization: tailoring the selection of samples sent to each Birchbox subscriber
• Full-size product recommendation: based on purchasing and browsing history, samples received, reviews, profile etc.
• Improvements to product and content search and sorting
• Prediction of subscriber churn, sample conversion, shop activation, etc.
• Working with analysts and other teams to deliver insights to inform major product and business decisions

A successful Data Scientist candidate at Birchbox will have:

• 1-3 years of experience as a data scientist
• Fluency in a scripting language such as Python for fast prototyping
• Strong understanding of classification, clustering and recommendation algorithms
• Ability to write complex SQL queries in short order
• Experience with Map/Reduce tools (e.g. Hadoop, Pig, Hive)
• Solid understanding of a wide range of open source data mining / machine learning / data visualization software packages (e.g. pandas, scikit-learn, matplotlib, Spark
• Deep working experience applying statistics and machine learning research and techniques to real-world data

Preferred:

• Proficiency in R, Matlab, or another mathematical language
• Familiarity with various factorization models (e.g. matrix factorization, factorization machines)
• Experience with integer programming, search technologies, natural language processing
• Experience with designing and deploying ETL to ingest data into data warehouse
• Knowledge of distributed algorithms and how to analyze them
• Java, Scala know-how