Slingshot AI
Slingshot AI is the team behind Ash, the first AI designed for mental health. Our mission is to make support more accessible and help people change their lives in the ways they want.
We’re building a world-class team by empowering individuals with the autonomy, flexibility, and support they need to do their best work. We dream big, iterate fast, and care deeply. If that sounds like you, we’d love to hear from you.
Our team spans machine learning, product, engineering, conversational design, clinical, growth, and operations, with offices in both New York City and London.
We're a well-funded Series A company, having raised $93M from Andreessen Horowitz, Radical Ventures, Forerunner Ventures, plus top-tier tech investors involved in ElevenLabs, Captions, Shopify, Plaid, Notion, Canva, Twitch, Airtable, and many others.
The role
We are seeking a PhD-level Data Scientist to join our Wellbeing Research team. This role is ideal for someone who is deeply fluent in language data/NLP, understands clinical research methods, and enjoys working on applied problems where scientific validity is as important as technical performance.
Reporting to Slingshot’s Head of Research, Caitlin Stamatis, you will play a central role in designing, analyzing, and interpreting studies that leverage natural language as a primary signal, from high-density, real-world mental health dialogue and self-report text to longitudinal usage data and platform metrics, helping translate complex language patterns into meaningful insights.
This is a rare opportunity to help build the scientific engine behind AI mental health at massive scale: turning rigorous research into product decisions that improve the lives of millions, with the ambition to ultimately reach billions. You’ll help define what “better” means, how we measure it, and how we deliver it responsibly.
About you:
PhD or Master’s in a relevant field, for example: Data Science, Computational Linguistics, Health Economics, Public Health, Quantitative Psychology, Cognitive Science, Clinical Science, or related.
Demonstrated ability to independently lead end-to-end analyses on real-world, high-dimensional data (from problem framing → execution → interpretation → recommendations)
Experience applying NLP methods in research or applied settings focused on mental health, psychotherapy, social processes or with large populations.
Solid statistical foundations and experience with observational study analysis, including high-density unstructured real-world data.
Proficiency in Python and common data science / ML libraries, that could be passed on for incorporation into a data processing pipeline.
Demonstrated expertise working with language data as a primary modality.
Key responsibilities:
Design and analyze language-focused studies in collaboration with mental health researchers, translating psychological constructs into quantitative, language-based features.
Develop and validate language-derived metrics against gold standards to measure mental health, behavior, and social processes.
Lead analysis of large-scale real-world text and conversational datasets using statistical and machine learning methods, including embeddings, LLM-based features, and psycholinguistic approaches.
Assess model behavior, bias, and limitations in sensitive contexts, and track longitudinal or within-subject language changes.
Translate insights into product impact, informing experiments, user experience improvements, and cross-functional communication to both technical and non-technical teams.
What we offer:
A chance to join a passionate tight-knit team working on something to change the world
Competitive compensation (we target 90th percentile)
Travel between our NYC / London offices
Usual startup perks like free lunch in our offices + generous learning budget
Generous budget to cover your personal therapy
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