DiscoverStartupsTricog HealthJobs at Tricog Health: Explore current Opportunities
Tricog Health company logo
Tricog Health
Actively Hiring
Quicker, Accurate, Affordable Healthcare Technology201-500 Employees
  • Top 10% of responders
    Tricog Health is in the top 10% of companies in terms of response time to applications
  • Responds within two weeks
    Based on past data, Tricog Health usually responds to incoming applications within two weeks
  • Growth Stage
    Expanding market presence

Jobs at Tricog Health

We are solution oriented and courageous enough to take on the problem across hardware, software, algorithms, and operations. Here you will get to see a large number of components collaborate to solve real world problems. You will get to work with PhDs with numerous papers and patents and see how they approach a problem.
Filter by
Team
Location
Type
Product

Product Manager

NewPosted yesterday

Product Manager

About us:
At Tricog, we are seeking a Product Manager to act as a crucial bridge between our commercial and
engineering teams. As our organization grows, the complexity of communication between those who
sell our products and those who build them increases.

Other

Project Manager

NewPosted 4 weeks ago

Project Manager

Role Overview

We are looking for a mid-level Project Manager with 2-4 years of experience to lead the end-to-end delivery of software and clinical product initiatives in a healthcare environment. This role sits between Associate and Senior PM levels and is expected to manage projects with cross-...

Engineering

Lead Mobile Engineer (Android / Flutter)

NewPosted 1 month ago

Lead Mobile Engineer (Android / Flutter)

  • Own the architecture and technical roadmap across our native Android and Flutter codebases, and make the trade-off calls that come with it.
  • Lead the design and delivery of complex features end to end, from technical design through production.
Engineering

Data Scientist

NewPosted 1 month ago

Data Scientist

  • Design and Implement AI Models: Develop, train, and evaluate machine learning and deep learning models for cardiac datasets and associated metadata.

  • Data Pipeline Development: Work with large, complex, and sometimes messy clinical datasets. Contribute to building robust and scalable data pipelines for data ingestion, cleaning, feature engineering, and labeling.