Data Science Lead

SKIMS is a solutions-oriented brand creating the next-generation of underwear, loungewear, and shapewear.

We set new standards with our game-changing product and are a driving force within pop-culture.

We are looking for an experienced Data Scientist to be a founding leadership member of our Data, Insights, and Loyalty team. In this role, you will help build data driven, analytics solutions to power core business processes for the entire company across domains such as customer/loyalty, retail product (merch/design/production/inventory management), and operations. You will also support emerging strategic initiatives such as growth/expansion, new business initiatives/channels, and novel applications of data / analytics / AI in existing business processes. Key deliverables for this role include building data products such as models/forecasts in addition to prototyping end user facing solutions. This role reports to the SVP, Data Insights and Loyalty.

Primary Responsibilities

·       Own research, development, and delivery of end-to-end data science and AI/ML solutions (with support from rest of team) for critical business processes for the organization, such as demand sensing/forecasting, customer lifetime value / propensities, product attribution, and operations forecasting

·       In partnership with SVP as well as the other leaders in the team (Sr Director, Analytics and Sr Director, Engineering), support development of analytical roadmaps that accelerate growth across all aspects of the business

·       Work with our technology partners and data engineering to ensure high-quality, usable data are captured to support reliable business-facing analytics

·       Build scalable methodology and tools to accelerate development of our data science practice, including partnering with data engineering to build production-grade data science pipelines

·       Support initiatives to build data and analytics competencies across the entire organization with the support of the data, insights, and loyalty team

Qualifications

·       4-6 years of experience in a data science or data analytics role, preferably working in a direct-to-consumer business

·       Proficiency with data science, mathematics, and statistical analysis with application to retail and apparel businesses

·       Advanced experience with pattern recognition and predictive modeling

·       Demonstrated ability to independently plan and execute repeatable analyses and data science models leading to actionable strategies

·       Excellent SQL skills with strong experience using statistical programming languages (Python, R, etc.) to manipulate data, draw insights from large datasets, and build production grade data science pipelines

·       Ability to work effectively in a dynamic, research-oriented manner on several concurrent projects

·       Creative thinker, adept at understanding a wide breath of retail analytics use cases and identifying the data and analytical methods necessary to make them into a reality

·       Demonstrated success working in a fast-paced, swiftly-changing startup environment

·       BA/BS in Math, Economics, Statistics, Analytics, Data Science, or other quantitative field highly desirable 

Benefits and Culture

·       100% Company Paid Healthcare (medical, dental, vision) 

·       Kind Body Fertility Benefits   

·       401(k) savings plan with up to 4% match 

·       Unlimited PTO  

·       Full Access to LinkedIn learning 

·       Employee Discounts  

Perks (HQ Location)

·       Free weekly catered lunch at HQ – M/W/Th  

·       Dog-Friendly office  

·       Free Swag Giveaways  

·       Annual Holiday Party  

·       Annual Summer Party  

·       Invitations to pop-ups and other company events  

·       Complimentary daily office snacks and beverages 

SKIMS is committed to continuously creating an inclusive environment for all employees and candidates, reflective of the rich diversity of the communities we serve. Equitable workplaces foster innovation and excellence, and in our commitment to culture of belonging qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity, gender expression, veteran status, or disability.