About Us:

Hippocratic AI has developed a safety-focused Large Language Model (LLM) for healthcare. The company believes that a safe LLM can dramatically improve healthcare accessibility and health outcomes in the world by bringing deep healthcare expertise to every human. No other technology has the potential to have this level of global impact on health. 

Why Join Our Team:

• Innovative Mission: We are developing a safe, healthcare-focused large language model (LLM) designed to revolutionize health outcomes on a global scale.

• Visionary Leadership: Hippocratic AI was co-founded by CEO Munjal Shah, alongside a group of physicians, hospital administrators, healthcare professionals, and artificial intelligence researchers from leading institutions, including El Camino Health, Johns Hopkins, Stanford, Microsoft, Google, and NVIDIA.

• Strategic Investors: We have raised a total of $278 million in funding, backed by top investors such as Andreessen Horowitz, General Catalyst, Kleiner Perkins, NVIDIA’s NVentures, Premji Invest, SV Angel, and six health systems.

• World-Class Team: Our team is composed of leading experts in healthcare and artificial intelligence, ensuring our technology is safe, effective, and capable of delivering meaningful improvements to healthcare delivery and outcomes.

For more information, visit www.HippocraticAI.com.

We value in-person teamwork and believe the best ideas happen together. Our team is expected to be in the office five days a week in Palo Alto, CA unless explicitly noted otherwise in the job description

About the Role

As a Junior Analyst at Hippocratic AI, you will be primarily responsible for data labeling (60-70%) and creating data reports (30-40%) to support the continuous improvement of our healthcare-focused LLM solutions. In this role, you’ll help ensure our data is meticulously labeled and evaluated, perform second-level reviews of externally labeled data, and create reports based on labeled data and patient call outcomes. Your work will directly influence the accuracy and reliability of Hippocratic AI’s solutions, helping maintain high standards of patient safety and experience.

You’ll collaborate with cross-functional teams—including engineering, product, and clinical experts—to troubleshoot data tasks, debug labeling complexities, and provide succinct insights. While the majority of your time will be spent on labeling and adjudicating data, you’ll also contribute to ad-hoc reporting and analysis to optimize our internal processes and model performance. Additionally, you will have extensive exposure to building a highly technical LLM product with lots of mentorship and growth opportunities.

Responsibilities

• Data Labeling & Quality Control

  • Accurately label data to support model training and safety analysis.

  • Conduct second-level reviews/adjudications of nurse-produced labels to ensure accuracy and consistency.

• Basic Analysis & Reporting

  • Gather relevant datasets by running SQL queries or by running Python scripts.

  • Produce weekly data summaries and reports to assist senior team members in decision-making.

  • Track and document metrics or issues that arise during labeling, contributing to process improvements.

• Collaboration & Debugging

  • Work closely with engineering and product teams to clarify labeling guidelines and address edge-case scenarios.

  • Communicate findings clearly and succinctly, highlighting patterns or problems for cross-functional teams.

Required Skills & Qualifications

• Bachelor’s degree (or equivalent experience) in Data Science, Statistics, Computer Science, or related field.

• Exposure (including through coursework) to python (preferably), R, or another scripting language

• Experience analyzing data and creating reports

• Strong attention to detail, with a track record of accurately following instructions and processes.

• Solid communication skills; able to convey findings to both technical and non-technical stakeholders.

• Ability to stay organized and manage multiple tasks in a fast-paced environment.

Preferred

• Previous experience in data labeling, data entry, or QA.

• Experience writing basic SQL queries

• Exposure to machine learning or AI projects (coursework or internships acceptable)

• Understanding of healthcare or clinical workflows

• Experience working in a startup or fast-growing company.