Sr. Data Scientist

Hims And Hers - London, England - Global - Construction & Infrastructure

Hims & Hers is the leading health and wellness platform, on a mission to help the world feel great through the power of better health. We are redefining healthcare by putting the customer first and delivering access to care that is affordable, accessible, and personal, from diagnosis to treatment to delivery. No two people are the same, so we provide access to personalized care designed for results. By normalizing health & wellness challenges and innovating on their solutions, we’re making better health outcomes easier to achieve. 

Hims & Hers is a public company, traded on the NYSE under the ticker symbol “HIMS.” To learn more about the brand and offerings, you can visit hims.com/about and hims.com/how-it-works . For information on the company’s outstanding benefits, culture, and its talent-first flexible/remote work approach, see below and visit www.hims.com/careers-professionals.

About the Role:

As a Senior Data Scientist at Hims & Hers, you are a core driver of technical execution and innovation within our data organization. You take complex business challenges and translate them into robust, scalable data products and machine learning models. You will be trusted to operate with high autonomy, owning your projects from the initial exploratory analysis through to production deployment.

In this role, you will work closely with Product, Engineering, and Business stakeholders to deliver solutions that optimize our operations, refine our marketing efforts, and enhance the customer experience. You will not only build powerful models but also help uphold the engineering rigor and standards of our data team.

You Will:

  • Build from Scratch: Thrive in a 0-to-1 environment. You are comfortable rolling up your sleeves to write complex SQL, engineer your own features, and deploy baseline models (heuristics or simple ML) quickly to prove value before iterating toward complex solutions.

  • End-to-End Execution: Own the complete model lifecycle, from data extraction and feature engineering to deployment, A/B testing, and ongoing performance monitoring.

  • Cross-Functional Collaboration: Partner closely with Engineering, Product, and Finance teams to define technical requirements and translate model outputs into clear,

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