Ribbon Health

< 10 Employees
< 10 Engineers
$1M - $2M Funding
Pre-Series A

Ribbon Health is a healthcare data platform. We provide accurate data to healthcare enterprises on doctors, insurance plans, and costs of care. Our vision is to ensure that every healthcare decision is cost-effective, convenient, and high-quality. We’re a small team backed by investors we love (e.g., YC, Box Group, SV Angel) and are growing quickly.

Ribbon Health photo 1

Why join us?
  • We’ve gone from zero to product market fit in the last 18 months, growing revenue at ~20% per month, becoming cash flow positive, and hitting >150% of our revenue goals. Now, we’re reinvesting for the next stage of growth.

  • Our product metrics have skyrocketed since we've started. The Ribbon data product now offers the highest-accuracy solution in the industry at a national scale of doctors (but still much more work to do!)

  • We’re lucky to work with an incredible, talented, & diverse team with strong start-up and data product experience, as well as a great team of investors including SV Angel, BoxGroup, and Y Combinator


Engineering at Ribbon Health
Engineering team and processes

How We Work

  • We believe in strong autonomy for every member of the engineering team
  • We collaborate closely with each other and try hard to ensure our most critical code is clean and usable by others
  • Once business context is provided, we believe the engineer should have the authority to own the design and build of the solution and to ask for help whenever needed

How We Code

  • We value code that is concise and simple
  • We strive to eliminate the need for “key-holders” — all critical code should be accessible, well-documented, and usable by everyone else.
  • We ship into production quickly and often. For big changes we peer-review; for smaller changes, we run basic tests before shipping. We follow the standard protocol for dev/prod, git branching, etc.

Tech Debt & Deadlines

  • We’ve gone to market and scaled quickly, and have incurred necessary tech debt because of that. As we mature, we are conscious to the status of our code base, where it needs improvement, and how quickly we can address the issues.
  • We strive to make time for critical functionality that will have a long term impact on the business. For such items, we value getting it right more than hitting the deadline.
Technical Challenges

Data Aggregation: We ingest a lot of data from various sources that have different data schemas; whether it be from public government data feeds, public websites, or data from our partners, we have to manage normalizing all of this data at scale. We then need to deploy logic that compiles and reconciles the different data sources that agree/disagree with each other. Last but not least, we spend time building the pipes that let this data flow into our system.

Data Engineering: We started off by using Postgres (worked great in the beginning) but as we approach billions of rows, we need a big data solution (e.g. EMR) to allow our data to flow through our ETL an order of magnitude faster than it currently does.

Machine Learning: We use models to predict the accuracy of various data points, ranging from whether a doctor is at a given location and whether a certain phone number is the right phone number to call. Once a model has been built, we need to spend considerable time in figuring out how to deploy it at scale.

Change Management: We allow clients to edit their data in a private silo. This has been a much desired and appreciated feature — and also one that gives us valuable data from each of our clients. (e.g., when a client deletes a location or phone number, that information helps us make our data better.) This provides a challenge in reconciling changes to our data, with various layers of complexity, across our core database and our clients’ private instances.

Solutions Engineering: Given the technical nature of our product, and the wide variety of use cases our clients have, we spend time working with our clients to ensure they are getting the most value out of working with Ribbon.

Projects you might work on
  • Building a new ETL for normalizing and ingesting all of our raw data that can handle our scale.

  • Exploring our raw data to see if there are insights we can use in our models, then leverage those features to build and ship an improved model to production

  • Extracting data from a super valuable data source that needs to be digitized or collected at scale

  • Building syncing functionality that allows our latest data to be programmatically synced with our clients edits

  • Become lead on the deployment of the Ribbon Platform to one of our biggest clients/revenue drivers.

Tech stack
Python
Django
SQL
PostgreSQL
AWS

Working at Ribbon Health

We live by six core culture values to ensure Ribbon is and will always be a great place to work. Learn more here: https://www.ribbonhealth.com/about-us

Generous Vacation
Gym/Fitness
Company Retreats
Work from Home
Health Insurance
Flexible Hours
Maternal/Paternal Leave
Free Food
Pet Friendly
401(k) Contribution

External Links

Interested in this company?
Skip straight to final-round interviews by applying through Triplebyte.

Apply