About us:

Oncora is an oncology software and data company dedicated to helping physicians and scientists collect and use real-world data to improve outcomes for cancer patients. Our machine learning algorithms, which are deployed in active clinical environments, accurately predict oncology outcomes such as unplanned hospitalization, survival, and recurrence. Our software products include: a clinical workflow and data entry system for oncology clinical care, a data warehouse that leverages connections to other healthcare software systems such as EMRs, PACS, to amass real-world, regulatory-grade oncology data, a machine learning platform to train and validate predictive models of key oncology events, a machine learning API to power external software tools, and a virtual clinical trial platform that allows pharma and device companies to leverage automated medical image analysis to advance new technologies in the fight to cure cancer. We work with world-leading cancer centers such as MD Anderson and Northwell Health, global device companies such as Varian Medical Systems, and innovative biopharma companies. Our team is mission-driven to its core.

About the role:  

We are looking for an experienced engineer to join our mission driven team to help develop our data platform that integrates and transforms multiple imperfect and messy data sources into clean, usable data so that we can learn from every cancer patient. 

As a main contributor on our Platform and Integrations team, you will play a vital role in developing and operating our core data platform and helping scale it to serve additional hospitals.

We are a small team trying to tackle a very large problem, so we need teammates that are ultimately accountable to themselves and continuously push themselves, the product and the organization forward.

What you will be doing:

• Developing pipelines to integrate new data elements into our normalized oncology schema
• Overseeing and monitoring our existing data infrastructure for stability, performance and accuracy
• Improving our data warehousing and reporting capabilities to support real-time analysis of tens of thousands of patients representing millions of data points
• Integrating standard and proprietary ontologies into our data enrichment processes
• Enhancing our de-identification capabilities to support machine learning and clinical research use-cases 
• Building reusable integrations with major clinical systems (e.g. EMR/EHRs)
• Deploying updates frequently to immediately improve the state of cancer care
• Providing constructive feedback to your team members through code and architecture reviews

About you:

• A solid base of software engineering experience, typically 1-5 years, with at least part of that time in data-focused roles or projects
• Fluency with a functional or imperative language (we use Python)
• Experience working with relational and non-relational databases (we use Postgres, MongoDB, Redis, and ElasticSearch)
• Tendency to seek simple, elegant solutions to complex problems
• Ability to analyze and optimize existing solutions
• A focus on writing understandable, testable, and maintainable code
• Experience working with asynchronous and distributed systems (we use RabbitMQ)
• Familiarity with modern containerized environments (we use Docker & Kubernetes)

Bonuses: 

• Experience with healthcare data standards and integration is a huge plus (HL7, FHIR, DICOM, etc.)
• Experience designing data models for analytical and transactional workloads

Compensation, Benefits, and Perks:

• Salary: $80-120k plus equity compensation
• 401k, health and dental insurance, flexible vacation policy, paid parental leave
• eBooks, online courses, workstation setup
• Events: happy hours, team dinners, conversations with oncologists (will return soon!)
• You get to work with smart, passionate people on a product that will have a direct impact on the quality of life for cancer patients

What to expect in the hiring process:

• Introductory phone call with the Head of Operations (30 minutes zoom call)
• Phone interview with VP of Engineering (60 min zoom call)
• Virtual onsite, including a pair programming session, engineering team meet, and co-founder meet (90-120 minute zoom call)
• Final stages, potential follow-up interviews, and offer discussions