Senior Data Scientist: ML Systems & Business Impact

K1 Industries; United States; Remote; USD 180,000 - 280,000; Full time

Benefits offered by this job

Competitive salary

Unlimited PTO

Comprehensive health benefits

ESPP

401k benefits with employer matching

Offsite team retreats

Job summary

Hims & Hers, a leader in health and wellness, seeks a senior ML engineer to architect scalable ML systems and production-grade data pipelines. You will balance speed with quality, design core ML infrastructure, and ensure deployments integrate with existing production platforms.

You will translate ambiguous business questions into actionable technical roadmaps, mentor senior engineers, and drive end-to-end lifecycle ownership of models in a cloud environment (AWS or GCP).

Qualifications

• 8+ years of experience building production ML systems with measurable impact.
• Strong Python/SQL expertise and deep data-science tooling experience.
• Experience deploying ML products in cloud environments (AWS or GCP).

Responsibilities

• Architect the 0-to-1 Foundation: design and implement automated ML systems with production code.
• Translate business needs into technical roadmaps delivering actionable results.
• Drive end-to-end deployment of ML products ensuring reliability and integration.
• Connect technical strategy with business goals to move core metrics.
• Define standards for model development and peer reviews with data partners.
• Own the full model lifecycle from data design to long-term value.
• Mentor Senior and Mid-level Data Scientists to raise technical bar.

Skills

Python

SQL

Pandas

NumPy

scikit-learn

PyTorch

XGBoost/LightGBM

AWS

GCP

CI/CD

ML Ops

Education

BS/MS/PhD in quantitative field

Tools

AWS

GCP

Kubeflow

CI/CD tooling

MLflow

Job description

Hims & Hers, a leader in health and wellness, seeks a senior ML engineer to architect scalable ML systems and production-grade data pipelines. You will balance speed with quality, design core ML infrastructure, and ensure deployments integrate with existing production platforms.

You will translate ambiguous business questions into actionable technical roadmaps, mentor senior engineers, and drive end-to-end lifecycle ownership of models in a cloud environment (AWS or GCP).