Staff Data Scientist

hims & hers

United States

Remote

USD 140,000 - 220,000

Full time

3 days ago
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Job summary

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.

Qualifications

  • 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.

Responsibilities

  • 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.

Skills

Python & SQL
Production ML
Leadership & Influence
CI/CD & MLOps
Cloud (AWS/GCP)

Education

BS/MS/PhD in quantitative field

Tools

pandas
NumPy
scikit-learn
PyTorch
XGBoost/LightGBM

Job description

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 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 (from customer acquisition to churn dynamics) into concrete technical roadmaps that deliver clear, actionable results
  • Drive Execution and Reliability: Lead the end-to-end deployment of ML products, ensuring they are not just accurate but robust, maintainable, and fully integrated into our production infrastructure
  • Connect Technical & Business Goals: Partner across Engineering, Product, and Business to ensure our technical strategy is solving the right business problems and moving our core metrics
  • Define Technical Standards: Act as a force multiplier by establishing the standards for model development. You will lead design docs and peer reviews that ensure our work is reproducible and integrates with the work of our Data and Analytics Engineering partners
  • Own the Results: Take accountability for the full model lifecycle, from the initial data design through to the long-term performance and business value of production systems
  • Mentorship & Coaching: Actively mentor Senior and Mid-level Data Scientists, elevating the technical bar and fostering a culture of continuous learning across the data organization.
Experience & Skills:
  • 8+ years of experience in Data Science or ML Engineering, with a proven track record of building production systems that deliver measurable business impact
  • Technical Mastery: High proficiency in Python and SQL. Expert-level experience with the Python data stack (pandas, NumPy, scikit-learn) and at least one major ML framework (such as PyTorch or XGBoost/LightGBM)
  • Systemic Problem Solving: Ability to work on unique issues requiring conceptual thinking and broad impact. You know how to build for long-term scalability while delivering immediate value
  • Leadership & Influence: Proven ability to influence without authority. You can translate complex technical logic into compelling narratives for executive leadership
  • Engineering Rigor: Experience with CI/CD, ML Ops, and managing the full lifecycle of models in a cloud-based production environment (AWS or GCP)
  • Education: BS, MS, or PhD in a quantitative field (Data Science, Statistics, Economics, CS, Applied Math, etc.) or equivalent field expertise
Preferred Qualifications:
  • 0-to-1 Execution: Experience taking the very first machine learning models in an organization from exploratory notebooks to reliable, automated production pipelines.
  • Advanced Business ML (Experience in 1-2 of the following):
    • Customer Behavior & Propensity
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