The Role

Hone is looking for a Senior Business Intelligence Analyst to join our team. In this role, you will report to the Sr. Director, Data, Analytics, and Machine Learning and you will work closely with business stakeholders to turn data into insights that drive strategic decisions. You’ll design dashboards, build reports, and develop thoughtful analysis to help teams across the company better understand performance and opportunities. This is a high-impact role where you’ll serve as a trusted analytics partner and shape how data is used to fuel our growth.

Primary Responsibilities

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

• Partner with Product & Engineering teams to understand their goals and translate them into metrics, reports, and dashboards.
• Build reporting products within the application.
• Build, maintain, and enhance core business dashboards using Power BI.
• Utilize AI to maximize efficiency.
• Use SQL and Python to extract, analyze, and transform data to support reporting and ad hoc analysis.
• Own the design and documentation of key business metrics, ensuring clarity and consistency across teams.
• Proactively identify trends, anomalies, and opportunities in data and share insights with stakeholders.
• Collaborate with Data Engineering and Analytics Engineering to ensure data models meet reporting needs and support self-service analytics.
• Contribute to the development of team-wide best practices for visualization, dashboard UX, and storytelling with data.
• Create training, documentation, and data literacy resources to enable others to access and interpret data effectively.
• Participate in sprint planning and help shape the BI roadmap by identifying high-value projects and recurring requests.
• Mentor and teach data-savvy stakeholders and serve as a subject matter expert in the BI toolset and analytics best practices.

Qualifications

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

• 5+ years of experience in business intelligence, data analysis, or a similar role.
• Advanced SQL skills and comfort working directly with raw tables to produce clean, performant queries.
• Intermediate Python skills to model and analyze raw tables.
• Hands-on experience with one or more modern BI tools (e.g., Power BI, Tableau, Looker).
• Strong data visualization and communication skills.
• Passionate about helping others understand and use data to drive better decisions.
• Experience working in cloud platforms (Azure, AWS, GCP)
• Familiarity with dbt or dimensional modeling concepts is a plus.
• Familiarity with healthcare, telehealth, or regulatory data (e.g., HIPAA) is a plus.
• 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

Compensation

$125,000-$140,000 DOE

The Role

We are looking for a Data Scientist Intern to join our Data, Analytics & Machine Learning team for Summer 2026. In this role, you will work on high-impact problems across product, clinical, and marketing domains. You will partner with data scientists, engineers, and business stakeholders to translate ambiguous problems into data-driven solutions and deliver measurable impact. This is a hands-on role where you will contribute across the full data science lifecycle—from data exploration and experimentation to modeling and stakeholder communication.

What You’ll Do

• Analyze large, complex datasets to uncover trends, patterns, and opportunities for product and clinical improvement
• Build and evaluate predictive models (e.g., classification, regression, forecasting) to drive decision-making
• Design and analyze experiments (A/B tests) to measure the impact of product and growth initiatives
• Partner with cross-functional teams to define problems, scope solutions, and deliver actionable insights
• Develop dashboards and visualizations to communicate key metrics and findings to stakeholders
• Collaborate with data engineers to ensure reliable data pipelines and scalable model deployment
• Present results and recommendations to technical and non-technical audiences

Minimum Qualifications

• Currently pursuing a Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Applied Mathematics, or a related field
• Strong foundation in statistics, probability, and machine learning fundamentals
• Proficiency in Python and common data science libraries (e.g., Pandas, NumPy, Scikit-learn)
• Experience writing SQL queries to analyze and manipulate data
• Strong problem-solving skills and attention to detail
• Ability to communicate complex ideas clearly and effectively

Preferred Qualifications

• Experience with experimentation, A/B testing, or causal inference
• Familiarity with machine learning frameworks (e.g., PyTorch, TensorFlow)
• Experience with data visualization tools (e.g., Plotly, Power BI, Looker)
• Exposure to working with large-scale or production datasets
• Interest in healthcare, longevity, or personalized medicine

Tools & Technologies

You may work with:

• Python (PySpark, Pandas, NumPy, Scikit-learn, PyTorch)
• SQL (Spark SQL or similar)
• Data transformation tools (e.g., dbt)
• BI & visualization tools (e.g., Power BI)

What You’ll Gain

• Hands-on experience working on production-grade data science problems
• Mentorship from experienced data scientists and exposure to industry best practices
• Ownership of projects with real business and clinical impact
• Experience working in a fast-paced, remote, cross-functional environment

Compensation

$20–$25/hour, 40 hours per week

Additional Requirements

• Must be able to work full-time (40 hours per week) during the internship
• This is a remote role based within the United States; candidates must be located within the U.S.
• This role is not eligible for current or future visa sponsorship (including CPT, OPT, or H-1B)

The Role

Hone is looking for a Senior Data Scientist, Healthcare Operations to join our data science team. In this role, you will report to the Sr. Director, Data, Analytics, and Machine Learning and focus on applying data science and AI to improve clinical outcomes and physician productivity across Hone’s virtual care platform.

You will work closely with clinical leadership, product, and engineering to design, build, and evaluate models and AI-powered workflows that support care delivery, reduce operational friction, and enable clinicians to practice at the top of their license. This is a senior individual contributor role focused on execution and delivery, with ownership over well-scoped, high-impact projects. This role is ideal for someone who thrives at the intersection of healthcare, data science, and applied AI—and who wants their work to have direct, measurable impact on patient care.

Primary Responsibilities

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

• Partner with Clinical, Medical, and Operations teams to apply data science and AI to longevity-focused care delivery, including hormone optimization, metabolic health, cardiovascular risk, and preventative care pathways.
• Develop and evaluate models and AI-driven workflows that support clinicians in delivering personalized, evidence-based longevity care at scale.
• Design and implement agentic AI workflows to assist with tasks such as longitudinal chart review, lab trend interpretation, clinical summarization, follow-up planning, and patient outreach.
• Analyze longitudinal patient data; including labs, vitals, prescriptions, and engagement signals; to identify opportunities to improve outcomes, adherence, and care consistency over time.
• Build analytical frameworks to measure clinical effectiveness, physician productivity, and patient safety in a virtual care environment.
• Collaborate with product and engineering teams to integrate AI-powered tools directly into telehealth clinical workflows, ensuring high usability and clinician trust.
• Define and track key performance indicators related to longevity outcomes (e.g., biomarker improvement, therapy adherence, patient engagement) and operational efficiency (e.g., time per visit, panel capacity).
• Evaluate and monitor AI-assisted clinical tools with a focus on reliability, bias, and real-world performance, incorporating clinician feedback and human-in-the-loop controls.
• Communicate insights, tradeoffs, and recommendations clearly to clinical leaders and cross-functional stakeholders.
• Contribute to shared standards and best practices for responsible, compliant AI use in longevity telehealth.

Qualifications

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

• 5+ years of professional experience in Data Science, Machine Learning, Analytics, or a related quantitative role.
• Master’s degree in a quantitative field (Statistics, Computer Science, Biomedical Informatics, etc.); advanced clinical training (e.g., MD, DO, RN, PA, NP) or equivalent healthcare experience is strongly preferred–we have multiple MDs in Data Science at Hone.
• Demonstrated experience working with healthcare data, clinical workflows, or care delivery systems.
• Demonstrated experience analyzing video with computer vision techniques
• Strong proficiency in Python for data analysis, modeling, and applied machine learning.
• Strong proficiency in SQL and experience working with complex, production healthcare datasets.
• Hands-on experience building and evaluating applied ML or AI systems in real-world settings.
• Familiarity with modern AI techniques, including LLM-based systems and agentic or workflow-driven AI approaches.
• Understanding of responsible AI considerations in healthcare, including safety, bias, and human oversight.
• Experience collaborating with cross-functional partners in product, engineering, and clinical teams.
• Strong communication skills, with the ability to translate complex technical concepts into clear, actionable guidance for clinical stakeholders.
• Ability to manage multiple projects independently and deliver high-quality work in a fast-paced environment.

The Role

Hone is looking for a Director, Business Intelligence to lead our BI function and manage a team of analysts supporting Finance & Operations, Product & Engineering, and Marketing & Customer Care. In this role, you will report to the Sr. Director, Data, Analytics, and Machine Learning and serve as a key thought partner in shaping how data informs decisions across the company.

You will own the BI roadmap and operating model, including self-service analytics, governance, stakeholder engagement, and delivery. This role is responsible for ensuring BI is both responsive to business needs and proactive in surfacing insights, while maintaining high standards for data quality, consistency, and usability.

This is a senior leadership role that blends strategy, people management, and hands-on analytical work.

Primary Responsibilities

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

BI Strategy & Roadmap

• Define and own the Business Intelligence roadmap, aligning BI initiatives with company priorities and data strategy.
• Drive the evolution of BI from ad hoc reporting to a proactive, insight-driven function.
• Identify opportunities where BI can better inform strategic, operational, and clinical decisions.

Team Leadership & Development

• Lead and develop a team of ~3-5 analysts across multiple business domains and experience levels.
• Set clear expectations for quality, timeliness, and impact.
• Coach analysts on analytical rigor, stakeholder management, and storytelling.
• Support hiring, onboarding, and long-term team growth planning.

Self-Service BI & Governance

• Own the self-service BI strategy, enabling stakeholders to answer common questions independently.
• Establish and enforce BI governance, including metric definitions, data ownership, access controls, and documentation.
• Partner with data engineering and analytics engineering to ensure BI is built on trusted, well-modeled data.

Stakeholder Partnership & Delivery

• Act as the primary BI partner for senior leaders across Finance, Operations, Product, Marketing, and Customer Care.
• Intake, prioritize, and manage BI requests using a clear, transparent process.
• Balance short-term stakeholder needs with longer-term strategic initiatives.
• Ensure BI deliverables are clear, actionable, and decision-oriented.

Hands-On Analysis & Execution

• Remain engaged in hands-on work as needed, including building dashboards, reviewing analyses, and tackling complex or high-impact analytical problems.
• Ensure dashboards and reports meet high standards for accuracy, usability, and design.
• Lead or support deep-dive analyses that inform strategic decisions.

Operational Excellence

• Track team throughput, quality, and stakeholder satisfaction.
• Identify and address bottlenecks in BI workflows, tooling, or collaboration.
• Improve processes to increase speed, reliability, and impact.

Qualifications

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

• 12+ years of experience in analytics, business intelligence, data, or a related field.
• 4+ years of experience managing and developing analytics or BI teams.
• Proven track record of owning BI strategy and delivering high-impact analytics at scale.
• Strong technical foundation in SQL and BI tools; ability to review and produce high-quality dashboards and analyses.
• Experience designing self-service BI solutions and metric governance frameworks.
• Strong project and stakeholder management skills, with the ability to juggle competing priorities.
• Experience partnering closely with senior leaders across multiple business functions.
• Excellent communication and data storytelling skills.
• Experience working with modern data stacks (e.g., dbt, cloud data warehouses, modern BI tools).
• Familiarity with product analytics, financial reporting, and operational metrics.
• Experience working closely with data engineering and machine learning teams.
• Exposure to experimentation or causal analysis frameworks.
• Experience in healthcare, telehealth, or other regulated industries.

The Role

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 modeling.

You will focus on building and applying statistical models, experiments, and analyses that inform marketing 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 Marketing teams to analyze and optimize the full customer funnel, including acquisition, conversion, retention, and churn.
• Build and maintain statistical models and analyses related to key marketing use cases such as attribution, LTV, CAC, churn prediction, cohort analysis, and conversion 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 marketing 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.

The Role

Hone is looking for a Sr Data Engineer to join our team. In this role, you will report to the Sr. Director, Data, Analytics, and Machine Learning and you will help build the pipelines and infrastructure that power analytics, reporting, and machine learning. You will also build an longevity ontology knowledge graph. You’ll work cross-functionally with engineering, data, and business teams to design and implement reliable, well-tested data pipelines and scalable models. This role is ideal for someone with 5+ years of experience who’s ready to deepen their impact and technical scope in a fast-paced, collaborative environment.

Primary Responsibilities

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

• Build, maintain, and optimize reliable data pipelines using SQL, dbt, and Python.
• Build, maintain, and optimize an ontology graph database using CosmosDB and Gremlin.
• Utilize agentic AI to automate pipeline development.
• Collaborate with Analytics Engineers, Data Scientists, Analysts and Software Engineers to move, transform, and structure data to meet business needs.
• Implement data testing, observability, and documentation to ensure data reliability and transparency.
• Participate in sprint planning and project estimation by breaking down work and communicating blockers.
• Support scalable data model development in the lakehouse, balancing performance, flexibility, and usability.
• Maintain and improve our data infrastructure, including orchestration and CI/CD pipelines.
• Identify opportunities to automate manual data workflows and reduce data-related tech debt.
• Monitor data quality and partner with engineering and product teams to fix upstream issues.
• Contribute to dbt model development and refactoring, following best practices and company conventions.
• Manage cloud data environments (e.g., Azure) and optimizing resource usage.
• Provide thoughtful code reviews and mentor junior teammates on data engineering concepts and tooling.

Qualifications

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

• 5+ years of industry experience in a data engineering, analytics engineering role, or ontology engineering role.
• 1+ years of industry experience building medical ontologies in a graph database (e.g. CosmosDB or Neo4j)
• Strong Python skills for ETL and automation tasks.
• Expert in SQL
• Proficiency in Gremlin
• Proficiency with dbt
• Proficiency with Git
• Experience working in cloud platforms (Azure, AWS, GCP)
• Exposure to event-based data systems (e.g., Kafka, Pub/Sub) or streaming architectures.
• Understanding of data architecture, dimensional modeling, and performance tuning.
• Experience writing CI tests, monitoring pipelines, and debugging data issues independently.
• Experience working in agile, cross-functional teams
• Bonus: Prior exposure to HIPAA or healthcare data
• 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

Compensation Range

$150,000-$180,000