Senior Manager, Data Science

About Honor

Our mission is simple: change the way we care for our parents so they can age safely at home.

How we accomplish that mission is anything but simple. Delivering reliable home care requires coordinating people, schedules, geography, skills, preferences, and changing needs across a complex operating environment.

Honor combines technology, operations, and the local expertise of our partner agencies to improve how care is delivered at scale. Our platform supports the caregivers who provide care, the teams who coordinate it, and the families who depend on it.

We are looking for a Senior Manager, Data Science to lead a team applying advanced data science and AI to some of Honor’s most important operational challenges.

About the role

You will lead the development of models and decision systems that improve how Honor matches caregivers and clients, constructs sustainable schedules, allocates capacity, prioritizes operational work, and responds to changing conditions.

This is not an analytics support role. Your team will work directly with Product, Engineering, and Care Operations to turn difficult operating problems into production systems that improve measurable outcomes.

You will contribute to Honor’s broader Data Science and Applied AI direction, help shape the team’s roadmap, and remain hands-on as a player-coach.

What you’ll do

• Help shape the Data Science and Applied AI roadmap, identifying where predictive modeling, optimization, experimentation, forecasting, causal inference, and modern AI can create the greatest impact.
• Lead the development of production models and decision-support systems that improve matching, scheduling, operational prioritization, and service reliability.
• Apply modern AI, including agentic workflows, to improve how teams analyze information, make decisions, and execute operational work.
• Partner with Product, Engineering, and Operations from problem definition through deployment, adoption, and iteration.
• Establish strong standards for evaluating, monitoring, and responsibly deploying machine learning and AI-enabled systems.
• Lead, coach, and grow the team while remaining hands-on in high-priority projects as a player-coach.

Examples of problems you may solve

• Improving caregiver-client matching while balancing fit, continuity, availability, and travel.
• Building more reliable and sustainable schedules for caregivers and clients.
• Using data science and AI to identify operational risks earlier and help teams focus where they can have the greatest impact.

About you

• 7+ years of experience in data science, machine learning, operations research, applied AI, or a related field, including 3+ years leading teams.
• Have built or led the development of models or decision systems that operated in production and influenced meaningful business or customer outcomes.
• Can determine whether a problem calls for prediction, optimization, experimentation, simulation, workflow redesign, an AI agent, or no model at all.
• Understand that successful applied AI requires more than choosing a model. It requires clear objectives, reliable data and tools, rigorous evaluation, thoughtful system design, and appropriate human oversight.
• Experience partnering with Product, Engineering, Operations, and senior business stakeholders on ambiguous, cross-functional problems.
• Comfortable working with imperfect operational data while maintaining a high standard for measurement and technical rigor.
• Can communicate clearly with technical, operational, and executive audiences.
• Have a bias toward action and an iterative approach to problem-solving. You are willing to inspect the data, understand the workflow, prototype solutions, and revise your view.
• Are an effective people leader who can set clear expectations, develop talent, prioritize work, and build a strong technical culture.

Helpful experience

Experience with marketplace, logistics, workforce, scheduling, healthcare, or other complex operating systems is especially valuable, as is experience with optimization, forecasting, recommender systems, causal inference, agentic systems, or AI evaluation.

A bachelor’s, master’s, or doctoral degree in a quantitative or technical field is welcome, but we care most about demonstrated ability, judgment, leadership, and impact.

Why this role is different

Many companies have interesting datasets. Honor has a dynamic operating environment in which technical decisions directly affect caregivers, care teams, families, and older adults. The opportunity is to build systems that do more than predict outcomes. They will help Honor decide what to do next, execute more effectively, and continuously learn from the results.