[All remote jobs](https://jobicy.com/jobs.md)[![hims & hers logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2023/11/e7b9b920-221.jpeg)](https://jobicy.com/company/hims-hers.md)[hims & hers](https://jobicy.com/company/hims-hers.md) # Sr. Data Scientist Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/hims-hers.md)ShareRemote from[USA](https://jobicy.com/job-region/usa.md)SalaryUSD 150k–180k / yrDepartment[Data Science & Analytics](https://jobicy.com/categories/data-science.md)EmploymentFull TimeExperienceSeniorPublished29 Oct 2026Apply before28 Nov 2026Listing views43Application actions3Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. AI Summary ## The role, at a glance. Hims & Hers is seeking a senior data scientist to develop scalable machine-learning products that improve operations, marketing, and customer experience. The role owns the full model lifecycle, from SQL-based exploration and feature engineering through deployment, experimentation, and monitoring. It requires strong production engineering practices across Python, cloud platforms, CI/CD, version control, and MLOps. The successful candidate will work autonomously with Product, Engineering, Finance, and business teams while mentoring junior data practitioners. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 4/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 5/5IndependentCollaborative AI insightThis is a senior, end-to-end applied ML role requiring 5+ years of experience, production deployment capability, and comfort operating in ambiguous 0-to-1 environments. The candidate must balance rigorous engineering execution with measurable commercial impact and cross-functional leadership. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job median (per year)Market rate$165,000US market range (per year)$150k–$210k0$231.00k AI insightThe employer discloses a base compensation range of $150,000–$180,000 USD per year, with a midpoint of $165,000. An estimated US market range for a senior data scientist with production ML and MLOps responsibilities is approximately $150,000–$210,000 annually; actual pay may vary by location, experience, and scope. ## Core skills Skills and capabilities most closely associated with this opportunity. [Python](https://jobicy.com/jobs?search_keywords=Python.md)[SQL](https://jobicy.com/jobs?search_keywords=SQL.md)[Machine Learning](https://jobicy.com/jobs?search_keywords=Machine%20Learning.md)[Feature Engineering](https://jobicy.com/jobs?search_keywords=Feature%20Engineering.md)[Pandas](https://jobicy.com/jobs?search_keywords=Pandas.md)[scikit-learn](https://jobicy.com/jobs?search_keywords=scikit-learn.md)[PyTorch](https://jobicy.com/jobs?search_keywords=PyTorch.md)[XGBoost](https://jobicy.com/jobs?search_keywords=XGBoost.md)[Time Series Forecasting](https://jobicy.com/jobs?search_keywords=Time%20Series%20Forecasting.md)[Causal Inference](https://jobicy.com/jobs?search_keywords=Causal%20Inference.md)[A/B Testing](https://jobicy.com/jobs?search_keywords=AB%20Testing.md)[AWS](https://jobicy.com/jobs?search_keywords=AWS.md)[GCP](https://jobicy.com/jobs?search_keywords=GCP.md)[MLOps](https://jobicy.com/jobs?search_keywords=MLOps.md)[CI/CD](https://jobicy.com/jobs?search_keywords=CICD.md) Sample interview questionsDescribe a machine-learning model you took from an initial business problem through production deployment.I begin by defining the decision the model will support and the success metrics with stakeholders. I build a reproducible baseline, validate data quality and leakage risks, then iterate on features and models using offline and, where appropriate, online evaluation. For production, I package the pipeline with versioned code and data assumptions, add monitoring for performance and drift, and document ownership and retraining criteria. How would you approach developing a churn or propensity model for a healthcare consumer platform? I would first define the prediction horizon, intervention window, eligible population, and business action tied to the score. I would build features only from information available before the prediction point, use time-based validation to prevent leakage, and evaluate both ranking quality and incremental business value. I would then partner with marketing and product teams to test interventions through controlled experiments rather than treating predictive accuracy alone as success. When would you choose a simple heuristic or baseline model over a more complex machine-learning approach? I would use a simpler approach when it can answer the business question quickly, is easier to explain, or performs comparably to a complex model. A baseline establishes whether additional modeling complexity creates enough incremental value to justify operational cost and maintenance. I would only move to more complex methods when evidence shows a material improvement in decision quality, scalability, or automation. How do you communicate model limitations and uncertainty to non-technical stakeholders? I connect limitations to the decision being made, using plain language and concrete examples of where the model is reliable or may fail. I communicate confidence intervals, key assumptions, fairness or data-coverage concerns, and expected trade-offs rather than presenting a score as certainty. I also recommend operational guardrails, monitoring thresholds, and experiment designs that make the remaining uncertainty manageable. What practices would you implement to make ML workflows production-ready? I would establish modular, tested code; Git-based review workflows; reproducible environments; automated CI/CD; and versioning for models, features, and training data. I would instrument pipelines for data-quality checks, latency, prediction distributions, drift, and business outcomes. Clear documentation, rollback procedures, access controls, and defined retraining ownership are also essential for reliable operation. Opportunity details ## About this role. 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](http://hims.com/about) and [hims.com/how-it-works](http://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](http://www.hims.com/careers-professionals). ### About the Role: As a Senior Data Scientist at Hims & Hers, you are a core driver of technical execution and innovation within our data organization. You take complex business challenges and translate them into robust, scalable data products and machine learning models. You will be trusted to operate with high autonomy, owning your projects from the initial exploratory analysis through to production deployment. In this role, you will work closely with Product, Engineering, and Business stakeholders to deliver solutions that optimize our operations, refine our marketing efforts, and enhance the customer experience. You will not only build powerful models but also help uphold the engineering rigor and standards of our data team. ### You Will: * Build from Scratch: Thrive in a 0-to-1 environment. You are comfortable rolling up your sleeves to write complex SQL, engineer your own features, and deploy baseline models (heuristics or simple ML) quickly to prove value before iterating toward complex solutions. * End-to-End Execution: Own the complete model lifecycle, from data extraction and feature engineering to deployment, A/B testing, and ongoing performance monitoring. * Cross-Functional Collaboration: Partner closely with Engineering, Product, and Finance teams to define technical requirements and translate model outputs into clear, actionable business insights. * Uphold Technical Standards: Write clean, modular, and production-ready code. Actively participate in peer code reviews and contribute to the team’s technical best practices. * Drive Project Delivery: Navigate technical ambiguity within your domain, breaking down complex project requirements into manageable, executable milestones. * Team Mentorship: Provide technical guidance and support to junior data scientists and analysts, helping them troubleshoot roadblocks and adopt best practices. ### Experience & Skills: * 5+ years of applied experience in Data Science or ML Engineering, with a track record of delivering production-ready models that drive measurable business value. * Technical Proficiency: Strong expertise in Python and SQL. Deep familiarity with the Python data stack (pandas, NumPy, scikit-learn) and standard ML frameworks (such as PyTorch, XGBoost, or LightGBM). * Engineering Rigor: Proven ability to build for production. Experience working in cloud-based environments (AWS or GCP) and familiarity with CI/CD workflows, version control (Git), and ML Ops principles. * Analytical Problem Solving: Strong ability to connect technical metrics to business outcomes. You know how to choose the right algorithm for the right problem rather than just the most complex one. * Communication: Excellent ability to explain technical concepts, model limitations, and analytical findings to non-technical stakeholders. * Education: BS, MS, or equivalent experience in a quantitative field (Data Science, Statistics, Economics, CS, Applied Math, etc.). ### 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- ### 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 [accommodations@forhims.com](mailto:accommodations@forhims.com) 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](https://www.hims.com/global-candidate-privacy-statement). 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