
hims & hers
Staff Data Scientist at hims & hers
$190,000–$230,000 / year
Apply for this positionRole overview
An at-a-glance view of the facts included with this Staff Data Scientist at hims & hers listing.
- Company
- hims & hers
- Location
- Remote, United States
- Work arrangement
- Remote
- Employment type
- Full-time
- Compensation
- $190,000–$230,000 / year
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Role overview
This job description has been rewritten in fresh language using the facts in the listing. Source credit and original listing details are available below.
The Staff Data Scientist will provide technical leadership across the data organization, choosing high-impact problems and turning ambiguous business needs into clear technical plans. The role connects business strategy with production machine learning, with a focus on scalable data products and measurable customer and business outcomes.
Responsibilities span establishing foundational automated ML systems and infrastructure, writing production code, and leading machine learning products from design through deployment and ongoing performance. The scientist will work with Engineering, Product, Business, Data, and Analytics Engineering teams to align technical decisions with business priorities and ensure systems are reliable, maintainable, and reproducible.
The role also sets model-development standards through design documents and peer reviews, owns the complete model lifecycle, and mentors mid-level and senior Data Scientists. The position is remote in the United States, full-time, with listed annual compensation of $190,000–$230,000. Benefits include salary and equity compensation, unlimited PTO, company holidays, quarterly mental health days, medical, dental and vision coverage, parental leave, an employee stock purchase program, 401(k) matching, and team retreats.
Role at a glance: Remote, full-time Staff Data Scientist role focused on production machine learning leadership, with annual compensation of $190,000–$230,000.
Responsibilities mentioned in the listing
- Design and implement automated ML systems and core infrastructure, making pragmatic architectural choices and contributing production code.
- Translate unclear business questions into actionable technical roadmaps.
- Lead end-to-end deployment of ML products, ensuring accuracy, reliability, maintainability, and integration with production infrastructure.
- Partner with Engineering, Product, and Business to align technical strategy with business needs and core metrics.
- Establish model-development standards through design documents and peer reviews, supporting reproducibility and integration with Data and Analytics Engineering.
- Own models from initial data design through ongoing production performance and business value.
- Mentor mid-level and senior Data Scientists and promote continuous learning.
Qualifications stated in the listing
- At least 8 years of experience in Data Science or ML Engineering, including a record of production systems with measurable business impact.
- Strong Python and SQL skills; expert-level experience with pandas, NumPy, and scikit-learn, plus at least one major ML framework such as PyTorch, XGBoost, or LightGBM.
- Ability to tackle novel, broad-impact problems, plan for scalability, and deliver near-term value.
- Demonstrated ability to influence without formal authority and explain complex technical concepts to executive leadership.
- Experience with CI/CD, MLOps, and full model lifecycle management in a cloud production environment using AWS or GCP.
- Bachelor’s, master’s, or doctoral degree in a quantitative field such as Data Science, Statistics, Economics, Computer Science, or Applied Mathematics, or equivalent field expertise.
- Preferred: experience taking an organization’s initial ML models from exploratory notebooks to reliable, automated production pipelines.
- Preferred: experience in one or two areas, including customer behavior or propensity modeling (such as churn, purchase propensity, lead scoring, or lifetime value), forecasting or anomaly detection, optimization for marketing spend, inventory, or resource allocation, or causal inference using methods such as quasi-experiments or difference-in-differences.
Full details from the source listing
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 Modeling: Building predictive models for churn, propensity-to-buy, lead scoring, or lifetime value (LTV) to directly drive targeted marketing and product interventions.
Applied Forecasting: Time-series forecasting, anomaly detection, or handling non-stationary data for demand or revenue planning.
Optimization: Building engines for marketing spend, inventory management, or resource allocation.
Causal Inference: Designing robust experiments (e.g., quasi-experiments, difference-in-differences) to measure true business impact beyond standard A/B testing.
Our Benefits (there are more but here are some highlights):
Competitive salary & equity compensation for full-time roles
Unlimited PTO, company holidays, and quarterly mental health days
Comprehensive health benefits including medical, dental & vision, and parental leave
Employee Stock Purchase Program (ESPP)
401k benefits with employer matching contribution
Offsite team retreats
We are committed to building a workforce that reflects diverse perspectives and prioritizes ethics, wellness, and a strong sense of belonging. If you're excited about this role, we encourage you to apply—even if you're not sure if your background or experience is a perfect match.
Hims considers all qualified applicants for employment, including applicants with arrest or conviction records, in accordance with the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance, the California Fair Chance Act, and any similar state or local fair chance laws.
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
Hims & Hers is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please contact us at [email protected] and describe the needed accommodation. Your privacy is important to us, and any information you share will only be used for the legitimate purpose of considering your request for accommodation. Hims & Hers gives consideration to all qualified applicants without regard to any protected status, including disability. Please do not send resumes to this email address.
To learn more about how we collect, use, retain, and disclose Personal Information, please visit our Global Candidate Privacy Statement.


