Job Description

Company Overview:

Cohere Health is a fast-growing clinical intelligence company that’s improving lives at scale by promoting the best patient-specific care options, using cutting-edge AI combined with deep clinical expertise. In only four years our solutions have been adopted by health plans covering over 15 million lives, while our revenues and company size have quadrupled. That growth combined with capital raises totaling $106M positions us extremely well for continued success. Our awards include: 2023 and 2024 BuiltIn Best Place to Work; Top 5 LinkedIn™ Startup; TripleTree iAward; multiple KLAS Research Points of Light awards, along with recognition on Fierce Healthcare's Fierce 15 and CB Insights' Digital Health 150 lists.

Opportunity Overview:

Last but not least: People who succeed here are empathetic teammates who are candid, kind, caring, and embody our core values and principles . We believe that diverse, inclusive teams make the most impactful work. Cohere is deeply invested in ensuring that we have a supportive, growth-oriented environment that works for everyone.

What you will do:

Deploy machine learning algorithms to uncover drivers, impacts and key influences to support our healthcare product, leadership and clinical teams by applying optimization and statistical methods on large data sets. Duties include:

• Design and implement solutions to address complex business questions using statistical methods, machine learning, or other analytical methods as needed.


• Apply advanced analysis techniques and statistical concepts to draw insights from massive datasets, create intuitive simulations, data visualizations, and business narratives.


• Work closely with process and design engineers, business intelligence engineers, data engineers, and technical product managers to obtain relevant datasets.


• Use gathered data sets to oversee and create models, develop and oversee scalable and reusable codebases for scalable data solutions.


• Review, communicate, and present data solutions results to business leaders and various stakeholders.


• Contribute to and supervise performance tracking; identify improvement opportunities among junior engineers; design and implement robust testing systems to align ML output to business outcomes.


• Supervise work and advise junior team members on scientific process and experimentation.


• Contribute to multiple work streams as expert advisor.

Your background & requirements:

Master’s degree in Data Science, Computational Linguistics, Machine Learning, or closely related quantitative field and three (3) years of professional machine learning or data science experience driving process automation in a healthcare setting using language models. Must have 3 years of experience (may be gained concurrently with above):

• Applying retrieval and relational extraction techniques to unstructured clinical notes and other patient health history documentation.


• Querying and reasoning over structured healthcare claims data.


• Leveraging AWS services to enable robust systems and processes across the ML lifecycle, including experimentation, training, evaluation, deployment, and monitoring.


• Leveraging Python, PyTorch, and HuggingFace for NLP tasks in healthcare.


• Leading small engineering teams to understand business problems, form falsifiable hypotheses, and apply robust experimentation to determine technical direction.

This position is remote and can be performed from any location within the United States.

We can’t wait to learn more about you and meet you at Cohere Health!

Equal Opportunity Statement: 

Cohere Health is an Equal Opportunity Employer. We are committed to fostering an environment of mutual respect where equal employment opportunities are available to all. To us, it’s personal.

The salary range for this position is $162,000 - $185,000 annually; as part of a total benefits package which includes health insurance, 401k and bonus. In accordance with state applicable laws, Cohere is required to provide a reasonable estimate of the compensation range for this role. Individual pay decisions are ultimately based on a number of factors, including but not limited to qualifications for the role, experience level, skillset, and internal alignment.

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