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Services Data Lead

Project Healthy Minds
CompanyProject Healthy Minds
CategoryData & Analytics
LocationNew York
RemoteRemote
EmploymentNot stated
LevelLead
SalaryNot stated by the employer
Posted21 Jul 2026
Last verified30 Jul 2026
SourceEmployer career page (lever)
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Description
About Project Healthy Minds Project Healthy Minds is a mental health nonprofit that runs like a tech startup. We are pioneering a first-of-its-kind model: applying technology to address one of the biggest social issues of our time: the growing mental health crisis. We believe in a simple but profound idea: that it should be as easy to find mental health services as it is to book a flight or a restaurant reservation. That's why we're building the world’s first digital marketplace for finding mental health services that are right for you.  To do that, we work with some of the most inspiring and influential leaders in America - business titans, tech entrepreneurs, clinicians and scientists, musicians, artists, athletes, media stars, policymakers, and more - because we believe that the world's most complex challenges require interdisciplinary teams and solutions. We are backed by a powerhouse of industry-leading Board of Directors and Advisory Council Members who are passionate, hands-on, and dive into the important work with us. Learn more at projecthealthyminds.com and @projecthealthyminds on social. About The Role WHAT WE'RE LOOKING FOR We're hiring a Services Data Lead to build a new set of mental health services for our platform, on a focused six-month engagement. We already have a schema and a curation pipeline, but are looking to upgrade both as we expand the depth and breadth of services we list on our platform. You'll consider the tradeoffs for the information users want and the challenges of acquiring/keeping it fresh, overseeing the candidacy -> screening -> tagging pipeline, direct a small bench of specialists, and work across product, engineering, and our service partners to measurably improve the platform’s offerings. You'll leave behind a documented, repeatable process, not just a better dataset. (We'll walk you through the specific scope and priorities during the process.) This is a great opportunity for someone passionate about mental health to help expand our platform offering and upgrade our operations in the process.  ENGAGEMENT & COMPENSATION • Term: Six months with defined scope and deliverables. Extension or conversion possible but not guaranteed. • Hours: ~32h/week preferred. • Location: Fully remote within the US. • Documentation and the playbook are important deliverables • Expect a short paid work sample. We’ll share some real-world examples of what we’re working to solve for. • Reports to the VP of Product. WHAT YOU'LL DO • Steward and evolve the services data schema & taxonomy. It’s poised to expand and change. You'll provide input about what to add, what to shift, and what these changes costs us to source and maintain — with judgment about how the data actually gets consumed downstream. • Own and iterate the curation pipeline. Sourcing, screening, and tagging. Make it better, faster, and (with the help of our engineering team) more automated. • Direct a small bench of data specialists. Set the quality bar, write the SOPs, and oversee the team to build out a substantial batch of services. • Work at the nexus of design, product, engineering, and service partners. You’ll liaise with multiple departments to identify the highest-value fields, refine candidacy review processes, and collaborate on how data is presented to users in the platform. • Advise on internal tooling. You'll be the sharpest user of our admin, ingestion, dedup, and QA workflows – work with our team to identify the most impactful improvements we can make. • Document the playbook. Transferable and clear — good enough that whoever inherits this doesn't have to reverse-engineer your thinking. WHAT YOU'LL BRING Must-Haves: • A working understanding of healthcare services data — ideally mental health specifically. You’ll need a sense for what consumers need to know prior to making a decision, where that data comes from, and how frequently it changes. • Strong data-schema and data-modeling
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