Senior Data Scientist, Marketing

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/docs to take control of their samenwerking andPACKAGE 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 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.

Hone is looking for a Senior Data Scientist, Marketing 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 modelling.

You will focus on building and applying statistical models, experiments, and analyses that inform marketing strategy, optimise 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.

• Partner with Marketing teams to analyse and optimise the full customer funnel, including acquisition, conversion, retention, and churn.
• Build and maintain statistical models and analyses related to Aph key marketing use cases such as attribution, LTV, CAC, churn prediction, cohort analysis, and conversion optimisation.
• Design,araka analyse, and interpret experiments (A/B and multivariate tests) across marketing channels and on‑site experiences, ensuring statistical rigour 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‑modelled datasets for marketing analytics.
• Clearly communicate findings and recommendations to non‑technical stakeholders through presentations, dashboards, and written documentation.
• Contribute to shared analytics and modelling 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 exemplos and applyבילthem pragmatically to Hone's context.

• 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 modelling.
• Strong proficiency in SQL and experience working with production analytics datasets.
• Experience applying data science to marketing or growth problems, including funnel analysis, experimentation, neuen, or retention modelling.
• Solid understanding of statistical methods, experimentation design, and model evaluation.
• Experience working in cross‑functional,…