Volver

Staff Data Scientist

CompraTica Empleos

EMP:Technology
London, England
Tiempo Completo
Remoto
0 vistas

Descripción

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.

Acerca de

the brand and offerings, you can visit hims.com/about and hims.com/how-it-works

For information on the company’s outstanding.

Beneficios

, culture, and its talent-first flexible/remote work approach, see below and visit www.hims.com/careers-professionals.About the Role:As a Staff Data Scientist at Hims & Hers, you are a technical leader and a "force multiplier" for our data organization

You do not just solve the most difficult problems; you identify which problems are worth solving to move the needle for our customers.

You will serve as a technical anchor, simplifying ambiguous problems into executable paths for the team.

In this role, you will bridge the gap between business strategy and production-ready machine learning.

Whether you are building frameworks for growth, optimizing our supply chain, or refining marketing attribution, you will ensure our data products are technically sound, scalable, and built to deliver measurable business results.

You Will:Architect the 0-to-1 Foundation: Lead the design and implementation of automated ML systems.

You know how to balance "doing it right" with "doing it fast," making pragmatic architectural choices (build vs.

buy, simple vs.

complex) while rolling up your sleeves to write production code and establish our core ML infrastructure.

Translate Business Needs: Turn ambiguous business questions (.

¿Te interesa? Aplicá ahora