Overview

About us:

Our mission is simple—we’re changing the way we care for our parents so they can live safely at home as they age. But how we accomplish our mission is anything but simple. Every day, we’re solving complex problems that don’t come with a playbook. Sound exciting? If you’re someone who shares our core values—Care Starts with Connection, Great Solutions Demand Empathy, When You Grow We Grow, Our Differences Propel Us—let’s talk.

Founded in 2014, Honor is now one of the fastest-growing, non-medical home care companies in the U.S. Why? We realized that by combining our amazing technology and operations with the local, personal touch of our partner agencies, we could make real progress transforming this fast-growing, $30BN industry. Honor’s unique approach is driving our leadership as an innovator—and our rapid growth. We have cutting-edge machine learning, a beautiful, well-designed app, and industry-leading design, paired with a strong sales, marketing, and support engine. But we’re not a tech company, we’re a human company. The technology we design just helps our people be even better at their jobs.

About the Work:

  • Leverage data to solve meaningful problems with appropriate complexity
  • Collaborate with a diverse team across engineering, care operations, product management, sales and marketing, and more.
  • Research operational/logistical problems and proactively identify potential solutions.
  • Lead the design, implementation, and evaluation of descriptive and predictive models.
  • Integrate machine learning into user-facing applications.
  • Mentor and provide technical oversight on teammates’ projects throughout the project lifecycle.

About you: 

  • Excellent communication skills with both technical and non-technical peers.
  • Excellent mathematical and statistical fundamentals, including a degree in a quantitative field (such as Computer Science, Mathematics, Statistics, Economics, Physics) or equivalent professional experience.
  • Wide-ranging professional experience solving complex business problems and shipping Python in a production environment.
  • 5+ years of industry experience.
  • Expertise with numerical software packages such as NumPy, scikit-learn, or Keras.
  • Able to manage product ambiguity, seeking clarity when possible.
  • Are accountable end-to-end for your own projects, through planning, deployment, maintenance, and monitoring. You spot and address potential issues early.

Bonus points if you have professional experience with: 

  • Designing systems to optimize portfolio allocation in a two-sided marketplace (E.g., ideal matches of people needing and providing care, automated financial incentives to staff remaining shifts, etc.)
  • Using survival analysis and related methods to evaluate risk of employee churn and to predict future high-performers
  • Collaborating with designers to develop effective methods of collecting data in order to quantify highly qualitative attributes, such as personality, taste preferences and perceived quality
  • Using NLP methods to build data products from a variety of unstructured data sources, including phone calls and website forms
  • Applying spatial statistics to incorporate geographic and regional differences in a variety of problem contexts

What’s next?

Honor is remote friendly! We’re hiring across the U.S., with an entirely virtual interview and onboarding process. No roles will require permanent relocation, but as conditions allow, we’ll have office space for in-person collaboration in our San Francisco Bay Area, CA and Austin, TX hubs. If you’re looking for a great job that offers you the opportunity to work from home, we’d love to talk to you.

Want to know more about why Honor is a great place to work? Check out our perks!

This role doesn’t sound quite right? Send this application to a friend who may be a fit and check out our other available roles!

Honor is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy), national origin, age, disability, genetic information, political affiliation or belief.