Data Scientist, ML - Storefront

OUR STORY

Quince was started to challenge the existing idea that nice things should cost a lot. Our mission was simple: create an item of equal or greater quality than the leading luxury brands and sell them at a much lower price. 

OUR VALUES

Customer First. Customer satisfaction is our highest priority.

High Quality. True quality is a combination of premium materials and high production standards that everyone can feel good about.

Essential design. We don’t chase trends, and we don’t sell everything.  We’re expert curators that find the very best and bring it to you at the lowest prices.

Always a better deal. Through innovation and real price transparency we want to offer the best deal to both our customers and our factory partners.  

Environmentally and Socially conscious.  We’re committed to sustainable materials and sustainable production methods. That means a cleaner environment and fair wages for factory workers.

OUR TEAM AND SUCCESS 

Quince is a retail and technology company co-founded by a team that has extensive experience in retail, technology and building early stage companies. You’ll work with a team of world-class talent from Stanford GSB, Google, D.E. Shaw, Stitch Fix, Urban Outfitters, Wayfair, McKinsey, Nike etc.

THE IDEAL CANDIDATE

We are seeking passionate individuals who are enthusiastic about transforming the way people purchase essential goods through innovative data science and AI solutions. We are a centralized data science team that optimize and automate the decision making and provide valuable and actionable business insights. As a Storefront Data Scientist at Quince, you will spearhead innovative data science solutions to elevate site personalization, ranking, search, and discovery. Your work will enhance the shopping experience, enabling you to drive meaningful improvements that shape the future of Quince.

RESPONSIBILITIES:

• Develop and apply machine learning and statistical models to enhance personalized site and app experiences, including product search, ranking, and recommendations.
• Build and optimize ranking features while contributing to end-to-end modeling pipelines using modern ML/AI techniques.
• Support model deployment, run experiments, and assist in monitoring model performance in production.
• Collaborate with product, business, and engineering teams to develop and implement data-driven solutions.
• Communicate findings by translating complex data insights into actionable recommendations for business stakeholders.
• Identify data gaps, define data requirements, and work with Engineering teams to improve data infrastructure and tracking.
• Share insights and best practices with Analytics and cross-functional teams to promote consistency in data-driven decision-making.
• Seek opportunities to automate processes and improve efficiency in model development and deployment.

DESIRED SKILLS:

• MS or PhD in statistics, mathematics, engineering, computer science or another quantitative field AND 2+ years of experience as a data scientist in relevant industry.
• Hands-on experience applying machine learning, predictive modeling, GenAI to developing consumer facing applications. 
• Deep knowledge in:
• Statistical and machine learning techniques.
• Data Science libraries in a programming or scripting language.
• Proficient in Python and SQL.
• Excellent communication and presentation skills.
• Experience with BI platforms such as Looker, Tableau etc.
• Move fast, be a team player, and kind.