Staff Data Scientist

hims & hers

. Lead the design and implementation of automated ML systems and core ML infrastructure .

Posted 9/24/2026full-timeRemote • United StatesLead💰 $190,000 - $230,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in leading the design and implementation of automated ML systems, ensuring robust model lifecycle management and integration with production infrastructure. Proficient in translating business needs into technical roadmaps while mentoring data science teams to drive measurable business impact.

Highest-signal resume keywords

Python ProficiencySQL ProficiencyExpertise in PandasExperience with PyTorchMLOps Experience

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data ScienceMachine Learning EngineeringModel Lifecycle ManagementAutomated ML SystemsProduction Code DevelopmentCI/CDCloud-Based Production EnvironmentsData DesignPerformance OptimizationStatistical Analysis

Soft Skills

Influencing Without AuthorityConceptual ThinkingNarrative Translation for ExecutivesMentoring

Tools & Technologies

AWSGCPScikit-learnNumPyXGBoostLightGBM

Certifications & Qualifications

BS in Quantitative FieldMS in Quantitative FieldPhD in Quantitative Field

Industry Keywords

Data ProductsSupply Chain OptimizationCustomer AcquisitionChurn AnalysisMarketing Attribution

Tech Stack

Tools & technologies

AWSCloudGoogle Cloud PlatformNumpyPandasPythonPyTorchScikit-LearnSQL

About the role

Key responsibilities & impact

Lead the design and implementation of automated ML systems and core ML infrastructure
Make pragmatic architectural choices while writing production code
Translate ambiguous business questions into concrete technical roadmaps
Lead end-to-end deployment of robust, maintainable ML products integrated into production infrastructure
Partner with Engineering, Product, and Business to align technical strategy with business goals and core metrics
Establish model-development standards through design documents and peer reviews
Ensure reproducibility and integration with Data and Analytics Engineering partners
Own the full model lifecycle from initial data design through long-term performance and business value
Mentor Senior and Mid-level Data Scientists
Build data products supporting growth, supply chain optimization, marketing attribution, customer acquisition, and churn analysis

Requirements

What you’ll need

8+ years of experience in Data Science or ML Engineering
High proficiency in Python and SQL
Expert-level experience with pandas, NumPy, and scikit-learn
Experience with at least one major ML framework, such as PyTorch or XGBoost/LightGBM
Ability to solve unique issues requiring conceptual thinking and broad impact
Proven ability to influence without authority
Ability to translate complex technical logic into compelling narratives for executive leadership
Experience with CI/CD and MLOps
Experience managing the full lifecycle of models in a cloud-based production environment using AWS or GCP
BS, MS, or PhD in a quantitative field or equivalent field expertise
Experience building production systems that deliver measurable business impact
Preferred: experience taking initial ML models from exploratory notebooks to reliable, automated production pipelines
Preferred: experience in 1–2 areas including customer behavior and propensity modeling, applied forecasting, optimization, or causal inference
Legally authorized to work in the U.S. without restriction for any employer
Must not require current or future immigration sponsorship by Hims & Hers to work in the U.S.

Benefits

Comp & perks

Equity compensation for full-time roles
Unlimited PTO
Company holidays
Quarterly mental health days
Comprehensive medical, dental, and vision benefits
Parental leave
Employee Stock Purchase Program (ESPP)
401k benefits with employer matching contribution
Offsite team retreats
Flexible/remote work approach