What we do

We’re fixing one of the most broken and costly pieces of the US healthcare system: medical billing.

Today, healthcare providers spend over $250B each year on administrative overhead just to get paid by insurance. Medical billing is expensive because it’s nuanced and hard - maybe ~100x harder than credit card payment processing - and because it’s traditionally done by armies of humans who track and manage complex rules and processes specific to individual insurance companies with little or no supporting software.

We’re rethinking medical billing from the ground up, using data science and machine learning to automate much of this complexity, so healthcare providers can get paid dramatically more easily and inexpensively.

Since finishing the Y Combinator W20 batch we've been funded by an incredible group of funds + angel investors. We have many more customers begging to use our product than we have bandwidth to serve, which is why we need you to help us scale!

The Role

At Candid Health, we’re searching for our first BI (Analytics) Engineer to bridge Analytics Engineering, Business Intelligence, and Data Analysis. As a key strategic investment for the company and product, you will be responsible for the data modeling and pipelines that enable our downstream data products. You will work closely with stakeholders across the business and play a foundational role in scaling the data team. Candid Health is positioned to unlock transformative technology for healthcare providers and the BI Engineer will play a critical role in that effort. 

What You’ll Do

• Own Data Modeling as a Practice: Build and deliver critical reporting, analytics, and data models for varying use cases. You will be the standardbearer for operational excellence in our efforts to extrapolate data for meaningful outcomes
• Set the Foundation for Future Data Work: We have ambitious plans to leverage data as a key component to our long term product strategy. This role will improve and scale our data infrastructure, enabling future ML and AI products
• Implement New Processes and Systems for Data Collection and Analysis: Deep dive with engineers to understand complex production data. Ensure that tooling and visualization platforms are accurate and available

Who You Are

• You have Bachelors degree in Math, Science, Engineering, or another data intensive field of study such as Library Science
• You have 4+ years of experience working in a Data Science, Data Analytics, or Data Engineering at a high growth startup or scaled technical organization
• You have experience working with data models, data pipelines and performing analysis 
• You have hands on experience working with common data warehouses such as Snowflake, BigQuery, or Redshift
• Enthusiasm for data modeling; hopefully you have opinions on slow changing dimensions
• You have a strong understanding of SQL and have used it in complex data environments
• You have well-developed opinions on modern data engineering and an ability to bring others up to speed
• You thrive in ambiguity and enjoy tackling complex tasks that have significant impact on the business at large
• You’re a clear and concise communicator; you enjoy the challenge of explaining complicated ideas in simple terms, both in-person and in writing.
• Experience or exposure with the broader set of technologies in our ecosystem: Google Cloud Platform (BigQuery), Metabase, Terraform, Python, DBT.

Pay Transparency

The estimated starting annual salary range for this position is $135,000 to $180,000 USD. The listed range is a guideline from Pave data, and the actual base salary may be modified based on factors including job-related skills, experience/qualifications, interview performance, market data, etc. Total compensation for this position may also include equity, sales incentives (for sales roles), and employee benefits. Given Candid Health’s funding and size, we heavily value the potential upside from equity in our compensation package. Further note that Candid Health has minimal hierarchy and titles, but has broad ranges of experience represented within roles

Back: modern Python (async, type annotated) ~mini services, Celery + Redis for task queues, Postgres.

Front: Typescript + React. Good use of hooks + styled components.

Infra: Containerize all the things. docker-compose locally, Kuberntes + Istio on GCP. Pretty sophisticated developer tooling + CI (Github Actions) given our size.