Senior Data Scientist, Product at Hone Health in Remote

About Hone

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:

• Fight for the Customer
• Execute Ruthlessly
• Communicate Candidly, Clearly, and Kindly
• Collaborate Selflessly
• Practice Calculated Risk-Taking
• Maximize Joy and 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 Senior Data Scientist, Product to join our growing data team. In this role, you will report to the Sr. Director, Data, Analytics, and Machine Learning and partner closely with Marketing, Growth, and Product stakeholders to improve customer acquisition, conversion, and retention through data-driven insights and modeling.

You will focus on building and applying statistical models, experiments, and analyses that inform product strategy, optimize funnel performance, and improve customer lifetime value. This is a senior individual contributor role with significant ownership over execution and delivery. This role is ideal for someone who enjoys translating business questions into machine learning solutions, shipping high-quality work independently, and collaborating cross-functionally to drive tangible results.

Primary Responsibilities

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

• Partner with Product & Engineering teams to analyze and optimize product engagement and the full customer funnel, including acquisition, conversion, retention, and churn.
• Build and maintain statistical models and analyses related to key product use cases such as A/B tests, cohort analysis, and conversion/retention optimization.
• Design, analyze, and interpret experiments (A/B and multivariate tests) across marketing channels and on-site experiences, ensuring statistical rigor and clear recommendations.
• Translate ambiguous business questions into well-scoped analytical projects with clear success metrics and timelines.
• Collaborate with data engineering and analytics engineering partners to define data requirements and ensure reliable, well-modeled datasets for marketing analytics.
• Clearly communicate findings and recommendations to non-technical stakeholders through presentations, dashboards, and written documentation.
• Contribute to shared analytics and modeling best practices within the data science team, including code quality, validation, and documentation.
• Support junior team members through informal mentorship, code review, and knowledge sharing where appropriate.
• Stay current on industry trends and techniques in marketing analytics, experimentation, and applied data science, and apply them pragmatically to Hone’s context.

Qualifications

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

• 5+ years of professional experience in Data Science, Analytics, or a related quantitative role.
• Master’s degree in Statistics, Mathematics, Economics, Computer Science, or a related field.
• Strong proficiency in Python for data analysis, statistics, and modeling.
• Strong proficiency in SQL and experience working with production analytics datasets.
• Experience applying data science to product or growth problems, including funnel analysis, experimentation, attribution, or retention modeling.
• Solid understanding of statistical methods, experimentation design, and model evaluation.
• Experience working in cross-functional, agile environments with marketing, product, or business stakeholders.
• Familiarity with version control (Git) and collaborative development workflows.
• Experience working in cloud-based data environments (e.g., AWS, GCP, or Azure).
• Strong written and verbal communication skills, with the ability to explain complex analyses to non-technical audiences.
• Ability to manage multiple priorities, work independently, and deliver high-quality work in a fast-paced environment.

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 for exempt employees
• 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, part-time employees, 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.