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Staff Data Scientist, AI/ML

Doximity · San Francisco, CA or Remote (U.S.) · US

Health Tech
Remote
Not yet analysed
Demand90
Career growth95
Healthcare fit45
Remote potential80
5-year outlook
The posted total compensation range is $170,000-$248,000 (salary + equity). Given the high demand for AI/ML talent in healthcare, salaries are likely to remain competitive and grow with experience, potentially exceeding $300k for senior roles in the next 3-5 years.
Clinical license
Not required
Applicant reach
moderate
Seniority
senior
Employment type
–
Date found
2026-08-26

Intelligence details

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Why this is worth applying to

Clinicians with strong data science and AI/ML backgrounds should consider this role, as it offers a chance to directly impact healthcare technology at scale. However, the 5+ year experience requirement and advanced technical skills make it a stretch for most clinicians without formal data science training.

Who should apply

Physicians, nurses, or allied health professionals with a master's or PhD in data science, computer science, or related fields, and at least 5 years of hands-on ML experience. Also suitable for healthcare professionals who have transitioned into data science roles and have a portfolio of AI/ML projects.

CV angle

Highlight clinical domain expertise as a differentiator—emphasize understanding of medical workflows, patient data, and healthcare challenges. Frame any clinical research or quality improvement projects that involved data analysis, and quantify impact. Showcase technical skills in Python, SQL, and ML frameworks, and mention any experience with LLMs or deep learning.

Skills to highlight

  • Python
  • SQL
  • PyTorch/TensorFlow
  • Machine Learning
  • Deep Learning
  • LLM Fine-tuning
  • Statistical Analysis
  • Data Visualization

Role summary

A senior data scientist role at Doximity, focused on building and optimizing AI/ML products for physicians using large healthcare datasets. The role involves leading data projects, collaborating with product teams, and informing data strategy.

Read the full posting

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