Services Researcher (LA)

Project Healthy Minds•Los Angeles, CA

About The Position

Project Healthy Minds is a mental health nonprofit that operates like a tech startup and is building a digital marketplace to help people find appropriate mental health services. The Services Researcher supports the expansion of the services directory into local markets, working with the Services Research Manager to ensure listings are accurate and meet screening criteria established by the Clinical Advisory Committee. The engagement is based in the United States, ideally in Los Angeles, and is approximately 20 hours per week, with the schedule set in coordination with the Services Research Manager. It begins with a 90-day contract, with the option to extend as additional locations are added. The hourly rate is $25 to $40, depending on experience.

Requirements

  • Experience conducting research where accuracy and source citations mattered, such as work at a 211 or resource directory, in fact-checking, on a civic data team, or in a library.
  • Comfort contacting unfamiliar organizations and obtaining clear answers from respondents.
  • Ability to follow written procedures closely and flag cases where the procedure does not fit the information found.
  • Strong organization in spreadsheets and careful attention to detail.
  • Comfort using AI tools and checking their output before relying on it.
  • Care for people seeking help, including attention to the consequences of inaccurate contact information or outdated listings.

Nice To Haves

  • Spanish or another language besides English.
  • Training in social work, counseling, or public health, or experience working in mental health services.

Responsibilities

  • Verify and complete service records, including addresses, hours, contact details, costs, insurance, and other data-model tags.
  • Assess services against screening criteria and quote evidence supporting each answer.
  • Find services not yet listed as the directory expands into new locations.
  • Identify services that do not fit the data model and explain what does not fit.
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