Senior Data Scientist - Healthcare AI (Remote)

CareDx; United States; Remote; USD 108,000 - 135,000; Full time

Benefits offered by this job

Health and welfare benefits

401(k) plan match

Employee Stock Purchase Plan

Pre‑tax commuter benefits

Gym reimbursement

Job summary

CareDx is seeking a Data Scientist II to develop clinically grounded AI and analytics solutions that support commercial, medical affairs, clinical research, and enterprise decision‑making.

The role combines applied data science, statistical modeling, machine learning, generative AI, and research collaboration. You will own workstreams from framing to deployment, with emphasis on transparent methods and stakeholder communication.

Qualifications

• BS/MS in Data Science, Computer Science, Statistics, Biostatistics, or related quantitative field.
• 5+ years in data science, with 3+ years in healthcare or regulated environments.
• Strong Python or R, SQL, and Git proficiency.

Responsibilities

• Own analytics and AI workstreams for next-best-action and field education capabilities.
• Develop interpretable ML, statistical, and generative AI solutions using structured and unstructured data.
• Build reproducible workflows and reusable components from research to production.
• Collaborate with clinicians, scientists, medical affairs, research teams, and business stakeholders to translate questions into rigorous analytical plans.
• Support abstracts, presentations, and research reports with privacy, security, validation, and documentation practices.

Skills

Python

SQL

Git

R

Education

BS/MS in Data Science / related field

Tools

Databricks

Cloud data platforms

Model lifecycle management

Job description

CareDx is seeking a Data Scientist II to develop clinically grounded AI and analytics solutions that support commercial, medical affairs, clinical research, and enterprise decision‑making.

The role combines applied data science, statistical modeling, machine learning, generative AI, and research collaboration. You will own workstreams from framing to deployment, with emphasis on transparent methods and stakeholder communication.