Hone is an online medical clinic at the forefront of transforming healthcare and enhancing longevity. We use cutting-edge scientific advancements to empower men and women to take control of their health and unlock their full potential. Our people are the heart of everything we do and drive our success. We approach every project through our brand values:

Champion Patient Needs
Execute Relentlessly
Communicate Constructively
Collaborate Generously
Turn Obstacles Into Opportunity
Give With Gratitude

Hone has been fully virtual from day one and will continue to be a remote-first employer.

Our Ideal Candidate

Our ideal candidate is a mission-driven, motivated multi-tasker who is invested in work that is fulfilling and impactful. They embrace change and tackle challenges with enthusiasm. They have an "all-in" disposition towards work, understanding that we are a fast-paced, high-growth organization with evolving priorities. They can excel at both independent tasks and collaborative work, leading with clear and candid communication. They exhibit humble leadership—the ability to drive initiatives forward while remaining excited about continuous learning and development opportunities. They feel strongly about being part of a team that advocates for people to live longer and better lives.

The Role

Hone is looking for a Staff Data Scientist to join our team. In this role, you will report to the Sr. Director, Data, Analytics, and Machine Learning and you will lead the design, development, and deployment of machine learning models that directly impact our core business and clinical outcomes. You will work cross-functionally with product, engineering, marketing, and clinical leaders to shape the roadmap for predictive analytics, experimentation, and personalization across the patient journey.

As a senior individual contributor, you will set the technical standard for modeling work, mentor teammates across data and engineering, and help scale our ML capabilities with production-grade infrastructure and governance. You will identify opportunities, scope ambiguous problems, and ship solutions that are both technically rigorous and operationally valuable. This is a high-impact, high-autonomy role for someone who thrives at the intersection of strategic thinking and deep technical execution.

Primary Responsibilities

Key responsibilities for this role include (but are not limited to) the following:

Lead and own end-to-end development of machine learning solutions—from opportunity identification and data exploration through modeling, deployment, monitoring, and iteration.
Partner directly with executive stakeholders (Product, Clinical, Customer Care, Marketing) to proactively identify, scope, and complete high-impact modeling opportunities (e.g., LTV, churn, attribution, conversion optimization, care plan personalization, recommendation engines).
Architect model governance standards and MLOps best practices in partnership with Data Engineering, including model registration, reproducibility, retraining workflows, performance monitoring, and alerting.
Mentor data scientists and machine learning engineers across the team, guiding technical development, model design, and production deployment strategies.
Collaborate closely with analytics engineers, data engineers, and software engineers to define data and infrastructure requirements.
Build reusable frameworks and tools that accelerate future modeling work across the company.
Serve as a trusted thought partner in quarterly and annual planning, helping define the data science strategy, investment roadmap, and team evolution.
Drive a culture of experimentation and statistical rigor across product teams, advising on A/B testing, power analysis, and causal inference methods where appropriate.
Regularly present complex modeling results to non-technical stakeholders in a clear, action-oriented manner.
Stay ahead of new ML techniques and tools, bringing practical innovations back into the Hone ecosystem.

Qualifications

In order to qualify for this role, candidates must meet the following criteria:

10+ years of progressive experience in Data Science
Master's degree in Statistics, Mathematics, Machine Learning, or related; PhD preferred
Expert in Python including machine learning, statistics, and visualization packages
Expert in RAG systems, LLMs, deep learning, and AI infrastructure
Knowledge of AI safety and responsible AI development
Expert at MLOps with experience shipping ML products in healthcare and/or at startups
Expert in SQL
Proficiency with Git
Experience working in cloud platforms (Azure, AWS, GCP)
Experience working in agile, cross-functional teams
Ability to multitask, prioritize, and adhere to deadlines while maintaining attention to detail and quality
Comfortable in a fast-paced, frequently changing environment
Creative problem-solving skills with a results-driven mindset
Can quickly learn new technology systems and communication tools
Ability to work autonomously and collaboratively

Benefits

Hone wants our team to be in the best condition of their lives, so we offer a range of benefits including:

A remote-first work environment
Competitive compensation and equity options
Health, dental, and vision insurance coverage
Short-term disability and basic life coverage
Flexible Spending Accounts (FSAs)
Lifestyle Spending Accounts (LSAs)
We follow federal holidays and have uncapped time off
Budget for the technology tools you need (laptop, monitor, and/or special software)
A focus on company-sponsored activities to foster engagement (both virtual and in-person)
Waived membership fees for any Hone team members utilizing Hone products

These benefits are available to full-time, regular employees, and not to independent contractors, temporary employees, or interns.

We are proud to be an equal-opportunity workplace committed to building a team culture that celebrates diversity and inclusion. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions. Please contact us to request accommodation.