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Salary
$128k – $197k per year
Location
Remote (United States)
Seniority
Senior · 5+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Lyra Health is the leading provider of Workforce Mental Health benefits, available to more than 15 million people worldwide. The company offers a full spectrum of care offerings, from preventive to severe.

About the Role:

Lyra is transforming mental health care by creating a frictionless experience for members, providers, and employers. We connect companies and their employees to mental health providers, therapy, and coaching programs that work.

We are looking for a self-driven, technical Data Scientist who cares about impact, ownership and innovation. In this role, you will work closely with Lyra’s Data, Product, Engineering, and Clinical teams on AI/ML initiatives that will enhance the experience of mental health patients and providers.

This Data Scientist role can be filled remotely anywhere within the US, as well as locally in our Burlingame, CA headquarters. Please note that remote-based candidates must be physically located within the United States.

Responsibilities

  • Work closely with Lyra’s Data, Product, Engineering, and other associated teams to enhance the Lyra platform to serve the needs of our providers and clients.

  • Become an expert in the diverse data sources we collect and partner with data engineers to build pipelines that apply clinical logic to raw data

  • Extract actionable insights, develop predictive and generative models, and implement rigorous evaluation frameworks to support product iterations

  • Complete time-sensitive ad hoc data requests for internal and external stakeholders

Qualifications

  • 5+ years of data analysis in an industry setting with a preference for individuals who have experience in product analytics in the AI/ML space and have partnered with engineering and product teams in prior roles.

  • Experience collaborating with cross-functional stakeholders across technical, business, and (ideally) clinical domains

  • Demonstrated understanding of statistical applications and methods (experimentation, probabilities, regression). Experience applying hypothesis testing in an industry or research setting.

  • Experience developing comprehensive analyses using irregular data from disparate sources. Willing to do whatever it takes to clean messy data prior to deriving insights.

  • Strong SQL proficiency. Experience writing complex queries with multiple schemas and tables. Preference for candidates who have experience creating views.

  • Graduate-level Statistics coursework with MS in a quantitative field is preferred (statistics, econometrics, biostatistics, quantitative social sciences).

Preferred Qualifications

  • Interest in public health a plus

  • Experience with AI/ML R&D, e.g. prompt engineering and RAG

  • Experience with Python, including cleaning and analyzing data as well as using Python to parse JSON structured data, call APIs, create user-defined functions, and automate.

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