Staff Data Scientist

hims & hers

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

Posted 11/3/2026full-timeRemote • United StatesLead💰 $190,000 - $230,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading the design and implementation of automated ML systems, ensuring scalability and business impact through effective collaboration with cross-functional teams. Proficient in managing the full model lifecycle and establishing standards for model development and deployment.

Highest-signal resume keywords

Python ProficiencySQL ProficiencyExpertise in PandasExperience with PyTorchMLOps Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ScienceMachine Learning EngineeringProduction Systems DevelopmentModel Lifecycle ManagementAutomated ML SystemsArchitectural DesignTechnical RoadmappingCI/CDCloud-Based EnvironmentsStatistical Analysis

Soft Skills

Influencing Without AuthorityConceptual ThinkingNarrative Translation for LeadershipMentoring

Tools & Technologies

AWSGCPXGBoostLightGBMNumPyScikit-Learn

Certifications & Qualifications

BS in Quantitative FieldMS in Quantitative FieldPhD in Quantitative Field

Industry Keywords

Machine LearningData EngineeringBusiness ImpactCustomer Behavior ModelingOptimization

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 frameworks for growth, optimize supply chain processes, or refine marketing attribution

Requirements

What you’ll need

8+ years of experience in Data Science or ML Engineering
Proven track record of building production systems delivering measurable business impact
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
Ability to build for long-term scalability while delivering immediate value
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
Preferred: experience taking initial machine learning models from exploratory notebooks to reliable, automated production pipelines
Preferred: experience in customer behavior and propensity modeling, applied forecasting, optimization, or causal inference

Benefits

Comp & perks

Competitive salary
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)
401(k) benefits with employer matching contribution
Offsite team retreats
Talent-first flexible/remote work approach