Staff Data Scientist

hims-and-hers; United States; Remote; USD 180,000 - 280,000; Full time

Benefits offered by this job

Health coverage

Parental leave

Retirement matching

Employee stock purchase program

Unlimited PTO

Team retreats

Job summary

Hims & Hers is seeking a senior ML leader to turn ambiguous business needs into production ML systems. You’ll establish ML infrastructure, guide data/engineering partners, and own models throughout their lifecycle—from data design to long-term performance.

You’ll design automated systems, translate questions into roadmaps, deploy robust ML products, and set lifecycle standards while mentoring teams and delivering measurable business impact.

Qualifications

• Eight+ years in data science or ML engineering with production systems.
• Proficient in Python and SQL with data-science stacks (pandas, NumPy, scikit-learn).
• Experience moving ML from exploration to automated production pipelines.
• Demonstrated ability to lead across data, engineering, and business teams.
• Bachelor’s or higher in a quantitative field; strong communication skills.

Responsibilities

• Design and build automated ML systems and core infrastructure.
• Translate business questions into technical roadmaps and models.
• Lead deployment of robust ML products integrated with production systems.
• Set model development standards and ensure reproducibility.
• Track model performance and business value over time.
• Mentor data scientists and influence cross-functional teams.

Skills

Python

SQL

Pandas

NumPy

Scikit-learn

ML Frameworks

Executive communication

Education

Bachelor's or higher in a quantitative field

Tools

PyTorch

XGBoost

LightGBM

CI/CD

MLOps

AWS or GCP

Job description

Role overview

Serve as a senior technical leader who turns ambiguous business needs into production machine-learning systems with measurable impact. You’ll help establish foundational ML infrastructure, guide technical direction across data and engineering partners, and remain accountable for models throughout their lifecycle, from data design to long-term performance.

Responsibilities

• Design and build automated ML systems and core infrastructure, making pragmatic choices about architecture, tools, and implementation.
• Translate business questions into technical roadmaps and models that support goals such as customer growth, supply planning, or marketing measurement.
• Lead deployment of robust, maintainable ML products integrated with production systems.
• Set model development standards through design documents, reviews, reproducibility practices, and collaboration with data and analytics engineering.
• Track model performance and business value over time, and drive improvements across the model lifecycle.
• Mentor data scientists and influence technical decisions across engineering, product, and business teams.

Requirements

• At least eight years of data science or ML engineering experience, including production systems that delivered measurable business results.
• Strong Python and SQL skills, fluency with tools such as pandas, NumPy, and scikit-learn, and experience with a major ML framework such as PyTorch, XGBoost, or LightGBM.
• Experience taking early-stage ML work from exploration to reliable, automated production pipelines.
• Experience with CI/CD, MLOps, and model lifecycle management in a cloud environment such as AWS or GCP.
• Ability to lead through influence, explain technical ideas to executive audiences, and balance scalable design with near-term value.
• Degree in a quantitative field or equivalent expertise.

Nice to have

• Experience in one or more areas such as customer propensity or churn modeling, lifetime value, forecasting, anomaly detection, optimization, or causal inference and quasi-experimental measurement.

Benefits and work setup

• Full-time compensation includes salary and equity.
• Benefits include health coverage, parental leave, retirement matching, and an employee stock purchase program.
• Unlimited paid time off, company holidays, quarterly mental health days, and team retreats.