Data Scientist II

About CareDx

CareDx is a leading precision medicine diagnostics company advancing care in transplant, specialty oncology, and cell therapy. Through innovative molecular diagnostics, digital health solutions, AI-powered data and analytics, and patient support services, CareDx partners with healthcare providers, patients, and biopharma organizations to inform clinical decision-making and improve patient outcomes.

At CareDx, every employee contributes to innovations that transform patient care and improve lives.

Job Overview

The Data Scientist II will develop clinically grounded, interpretable AI and analytics solutions supporting commercial, medical affairs, clinical research, and enterprise decision-making. This role combines applied data science, statistical modeling, machine learning, generative AI, and research collaboration.

Key Responsibilities

• Own analytics and AI workstreams for next-best-action and field education capabilities, translating integrated data into actionable recommendations.

• Advance literature intelligence workflows, including search, retrieval, synthesis, evaluation, and validation of AI-generated outputs.

• Develop interpretable machine learning, statistical, and generative AI solutions using structured and unstructured clinical, laboratory, commercial, and enterprise data.

• Build reproducible workflows and reusable components progressing from research prototypes to reliable applications and decision-support tools.

• Lead analytics research proposals and collaborations, including cohort definition, analysis planning, modeling, interpretation, and communication of results.

• Partner with clinicians, scientists, medical affairs, research teams, and business stakeholders to translate questions into rigorous analytical plans and defensible results.

• Support abstracts, presentations, and research reports while applying privacy, security, validation, and documentation practices.

• Contribute to forecasting, Promotion Effectiveness, and Digital Product Impact initiatives.

• Perform exploratory analysis, feature engineering, model development and evaluation, sensitivity testing, and scenario analysis using Python or R and SQL.

• Collaborate with data and application engineers on pipelines, version control, testing, deployment readiness, monitoring, and maintenance; document data lineage, assumptions, limitations, and recommendations.

Qualifications

• Bachelor of Science (BS) or Master of Science (MS) degree in Data Science, Computer Science, Statistics, Biostatistics, Bioinformatics, or a related quantitative field.

• 5+ years of experience in data science, machine learning, advanced analytics, AI engineering, or a related role, including 3+ years in healthcare, diagnostics, biotechnology, clinical research, life sciences, or another regulated environment.

• Strong hands-on proficiency in Python or R, SQL, and Git-based development workflows.

• Experience developing and validating predictive, descriptive, statistical, or machine learning models using real-world clinical, EHR, laboratory, research, or other complex longitudinal data.

• Ability to produce audit-ready documentation covering data lineage, methods, assumptions, testing, validation, and model limitations.

• Strong written and verbal communication skills and the ability to collaborate across technical, scientific, clinical, and business teams.

Preferred Qualifications

• Experience with AI-enabled search, natural language processing, literature intelligence, retrieval-augmented generation, or document synthesis.

• Experience moving analytical prototypes into user-facing or production workflows, including testing, monitoring, and ongoing support.

• Familiarity with Databricks, cloud data platforms, model lifecycle management, and modern analytics application frameworks.

• Experience contributing to clinical research deliverables such as protocols, abstracts, presentations, manuscripts, or analytical reports.

How We Work

• Curiosity: Start with Why

  We understand why a project matters, what problem we are solving, whom it helps, and what success looks like. We ask thoughtful questions, align early, and move forward with confidence.

• Accountability: Extreme Ownership

  We take responsibility for what we build and deliver. We communicate risks early, follow through on commitments, and help resolve problems rather than waiting for detailed direction.

• Transparency: Default to Share

  We proactively share context, decisions, progress, and lessons learned. We document and demonstrate our work so others can build on it.

• Empowerment: Amplify Others

  We succeed as a team. We collaborate openly, recognize the contributions of others, and give credit generously.

• Resilience: Learn Loudly

  We treat mistakes and unexpected outcomes as opportunities to improve. We focus on solutions, identify root causes, and share what we learn.

Additional Details

Every individual at CareDx has a direct impact on our collective mission to improve the lives of organ transplant patients worldwide. We believe in taking great care of our people, so they take even greater care of our patients.