Staff Data Scientist - Remote ML Systems & Growth

Jobicy; United States; Remoto; USD 140.000 - 220.000; Tempo pieno

Descrizione del lavoro

Hims & Hers is seeking a Staff Data Scientist to lead and scale our data organization. You will architect automated ML systems, balance speed with correctness, and act as a force multiplier across engineering and product to deliver measurable business impact.

You will translate business needs into technical roadmaps, own the full model lifecycle, and mentor a team of data scientists while ensuring robust, scalable, and production-ready solutions that move key metrics.

Competenze

• 8+ years of experience in data science or ML engineering.
• Proficiency in Python and SQL; strong data stack experience.
• Experience deploying ML systems in production (CI/CD, MLOps).
• Cloud experience with AWS or GCP; strong communication and leadership.

Mansioni

• Architect end-to-end automated ML systems and infrastructure.
• Translate business questions into technical roadmaps with tangible outcomes.
• Lead deploys of ML products; ensure reliability and integration with production.
• Collaborate with engineering, product, and business to align technical and business goals.
• Define and uphold standards for model development; drive reproducibility and reviews.
• Own model lifecycle from data design to long-term performance and value delivered.
• Mentor senior and mid-level data scientists to raise technical bar.

Conoscenze

Python & SQL

Production ML

Leadership & Influence

CI/CD & MLOps

Cloud (AWS/GCP)

Formazione

BS/MS/PhD in quantitative field

Strumenti

pandas

NumPy

scikit-learn

PyTorch

XGBoost/LightGBM

Descrizione del lavoro

Hims & Hers is seeking a Staff Data Scientist to lead and scale our data organization. You will architect automated ML systems, balance speed with correctness, and act as a force multiplier across engineering and product to deliver measurable business impact.

You will translate business needs into technical roadmaps, own the full model lifecycle, and mentor a team of data scientists while ensuring robust, scalable, and production-ready solutions that move key metrics.