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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