Data Science Intern
Journey ClinicalNew York, NY
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Job Description
Journey Clinical is on a mission to transform the growing mental health crisis by accelerating the adoption of frontier treatments that lead to lasting improvements in clinical outcomes. We have built a turnkey healthtech platform to safely and effectively expand access to a powerful modality known as Psychedelic-Assisted Psychotherapy, starting with Ketamine-Assisted Psychotherapy (KAP). In our patient-centered collaborative care model, licensed psychotherapists in the network take on the psychotherapy, while Journey Clinical's in-house medical team takes on patient eligibility, treatment plan and outcome monitoring. Our platform gives psychotherapists passionate about PAP the infrastructure and support required to become empowered KAP providers, while enabling higher standards of patient care and enhanced clinical outcomes.
We have recently closed a successful Series A round led by Union Square Ventures, and are backed by a number of top-tier investors including AlleyCorp, Fifty Years, Able Partners, Gaingels, Palo Santo, PsyMed Ventures, Coalition Operators, Christina Sass co-founder of Andela, Edvard Engesæth, MD co-founder of Nurx and, Hans Gangeskar co-founder of Nurx.
We are building an open-minded and inclusive workplace where you will have the opportunity to grow and collaborate with a diverse team of high performing individuals. Our team combines extensive experience in business and healthcare. We are mission driven and strive to make the workplace stimulating, ethical, rewarding, and fun. Together, we will be working at the cutting edge of a groundbreaking field that is reshaping mental health and we will make a direct impact on people’s lives.
What You'll Do
- Analyze user data and build insights to drive business decisions
- Create dashboards and reports for various teams
- Develop machine learning models and automated solutions
- Collaborate across teams on analytics projects
Must-Haves
- Currently pursuing or graduated from a Bachelor's or Master's degree in Data Science, Statistics, Computer Science, or related field
- Strong SQL skills and experience with data analysis
- Strong Python knowledge and machine learning knowledge
- Experience with Tableau or similar data visualization tools
- Good communication skills and ability to present insights to stakeholders
- Autonomous self-starter who thrives in a fast-paced startup environment
- Interest in healthcare, mental health, or clinical research
Nice-to-Haves
- Previous internship or project experience in healthcare analytics
- Understanding of user behavior analytics and engagement metrics
20-40 hrs/week
~90 days duration
This internship is based in our New York office with flexibility for remote work as needed.
Are you a data-driven student who thrives in fast-paced environments, loves solving problems with analytics, and is passionate about improving access to mental health care? We're hiring a Data Science Summer Intern to drive key analytics initiatives that directly impact patient outcomes and business growth. In this role, you'll create dashboards, analyze user behavior across our platforms and build machine learning models. You'll work cross-functionally with Product, Clinical Operations, Growth, and Success teams to deliver insights that guide strategic decisions.
Why join this team? We're a data-driven, mission-aligned analytics team that believes in rapid iteration, high ownership, and constant learning. We care deeply about empowering mental health providers and patients — and we operate with transparency, curiosity, and collaboration. You'll have the freedom to explore data, the support to build impactful solutions, and the clarity to measure real outcomes in revolutionary mental health treatment.
Journey Clinical is committed to creating a diverse and inclusive workplace. We encourage applications from all qualified candidates regardless of race, gender, age, religion, sexual orientation, or disability status.
Automate your job search with Sonara.
Submit 10x as many applications with less effort than one manual application.