Informatics Scientist - Cardiology AI at Tempus

| Chicago
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Passionate about precision medicine and advancing the healthcare industry?

Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time.

Tempus Insights is our business to develop, validate and launch new predictive tests, in oncology, cardiology and new disease areas, by leveraging our clinical + molecular + imaging data to provide novel insights to clinicians and patients.

We are seeking a highly motivated and capable informatics scientist with extensive experience and interest in healthcare statistical analysis to join our team and lead our efforts to secure regulatory approval for novel AI algorithms in cardiology. This position requires experience with algorithm validation, statistical analysis, scientific writing and algorithm validation. Top candidates will also have experience with cardiology. 

Duties and Responsibilities:

  • Lead efforts to validate predictive algorithms in cardiology and submit those AI algorithms to the FDA 
  • Design, develop and document statistical analyses for AI algorithms to ultimately submit those algorithms for FDA approval
  • Collaborate with scientists, and clinicians to design and perform analyses on cardiology clinical, imaging and molecular data in order to improve quality of care.
  • Work in interdisciplinary groups of scientists, engineers, and product developers to translate research into clinically actionable insights for doctors and patients.
  • Produce high quality and detailed documentation for all projects.
  • Develop and implement rigorous testing and validation infrastructure to support the use of predictive algorithms in clinical care.

Required Experience:

  • Ph.D. or Masters in Biostatistics, Statistics, Epidemiology or a related field
  • Computational skills using Python and R.
  • Understanding of FDA validation protocols and how to bring scientific ideas to market

Ideal candidates will possess:

  • 2-5 years experience working with healthcare algorithms to improve patient care
  • Self-driven and works well in interdisciplinary teams
  • Background in predictive or prognostic algorithm development
  • Strong background in the development of statistical models

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Technology we use

  • Engineering
  • Product
  • Sales & Marketing
    • JavascriptLanguages
    • PythonLanguages
    • SqlLanguages
    • AWSLanguages
    • ReactLibraries
    • ReduxLibraries
    • Node.jsFrameworks
    • Microsoft SQL ServerDatabases
    • MySQLDatabases
    • PostgreSQLDatabases
    • SQLiteDatabases
    • tableuAnalytics
    • JIRAManagement
    • SalesforceCRM

Location

600 WEST CHICAGO AVENUE, Chicago, IL 60654

An Insider's view of Tempus

What makes someone successful on your team?

We value creativity in ideation, autonomy in execution, and a healthy tendency to always question the status quo.

Ash

Lead Data Scientist

What are Tempus Perks + Benefits

Culture
Volunteer in local community
Friends outside of work
Eat lunch together
Daily stand up
Open door policy
Team owned deliverables
Team based strategic planning
Group brainstorming sessions
Pair programming
Open office floor plan
Health Insurance & Wellness Benefits
Flexible Spending Account (FSA)
Dental Benefits
Vision Benefits
Health Insurance Benefits
Life Insurance
Wellness Programs
Onsite Gym
Retirement & Stock Options Benefits
401(K)
Company Equity
Child Care & Parental Leave Benefits
Generous Parental Leave
Vacation & Time Off Benefits
Unlimited Vacation Policy
Generous PTO
Paid Volunteer Time
Paid Holidays
Perks & Discounts
Beer on Tap
Casual Dress
Commuter Benefits
Company Outings
Stocked Kitchen
Some Meals Provided
Happy Hours
Relocation Assistance
Fitness Subsidies
Professional Development Benefits
Diversity Program
Lunch and learns
Promote from within
Time allotted for learning
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