Senior AI/ML Data Scientist

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This position is based in Basel, and relocation assistance is not available.

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Senior AI/ML Data Scientist This role is based in the Digital Endpoints and Patient-Centered Solutions (DEPCS) team, the innovative digital, AI, and tech function within Roche Product Development Data Sciences (PDD).

You collaborate cross-functionally with teams including, but not limited to, clinical scientists, digital business leads, biostatisticians, and biomarker leaders, to integrate machine learning models into Roche platforms and clinical workflows.

You bring excellent communication, problem-solving, and teamwork skills, with a track record of delivering innovative machine learning solutions aligned with business needs, and the ability to work independently as well as in a cross-functional team.

Operating across the Science of Medicines and Operations, DEPCS is responsible for embedding patient-centered and AI-enabled digital solutions into the fabric of clinical research.

By integrating data science, measurement science, and digital product thinking, DEPCS delivers scalable and regulatory-ready innovations that enhance trial design, evidence generation, and clinical value of Roche medicines.

Responsibilities You analyze sensor time-series, biological, and clinical data to generate insights supporting decision-making in clinical development. You transform raw sensor data from varied wearable platforms into interpretable digital measures through robust signal processing, feature engineering, and algorithm development.

You design and implement advanced machine learning algorithms tailored to clinical trial data, ensuring adherence to best software engineering practices, comprehensive documentation, and validation protocols to safeguard scientific rigor.

You design and apply advanced Causal ML methodologies to clinical trial and observational data to support robust evidence generation and decision-making.

You present technical insights to both scientific and non-technical audiences and contribute to the publication of findings and to internal knowledge development efforts and also maintain awareness of trends in ML, digital biomarkers, and clinical AI.

Qualifications You hold an MSc or PhD (preferred) in Computer Science, Machine Learning, Statistics, Electrical Engineering, Biomedical Engineering, or a related field and have 6+ years of experience in machine learning, signal processing or AI in biomedical, pharma, or healthcare innovation settings.

You have expertise in sensor data analysis and signal processing, causal inference, machine learning, foundation models, statistics, and probabilistic modeling, with exposure to image analysis and computer vision.

You have experience in bridging advanced sensor analytics with rigorous statistical frameworks, including the evaluation of psychometric properties to ensure valid evidence generation and you are committed to the principles of reproducible research, ensuring that sensor-derived datasets are harmonized, documented, and audit-ready.

You are proficient with scientific programming languages and familiar with high-performance computing infrastructure and machine learning experiment monitoring workflows and have expertise in best software engineering practices and production infrastructure, including MLOps frameworks and Agile, with exposure to regulated software development as a plus.

You demonstrate capacity for independent thinking and the ability to make decisions based upon sound principles and you bring excellent strategic agility, including problem-solving and critical thinking skills, and agility that extends beyond the technical domain.

You demonstrate respect for cultural differences when interacting with colleagues in the global workplace and have excellent verbal and written communication skills, specifically in the areas of presentation and writing, with the ability to explain complex technical concepts in clear language.

Preferred Skills Core Technical Skills & DevOps: Proficiency in Python, Git, Docker, shell scripting, high-performance computing (Slurm/LSF), and ML experiment management, utilizing agile frameworks like Scrum via GitLab or Jira.

Sensor Data & AI Expertise: Hands-on experience analyzing remote, error-prone sensor data (unattended DHTs) and developing agentic systems or LLM orchestration frameworks (e.g., LangChain, AutoGen).

Compliance, Documentation & Impact: Experience validating ML models for regulated or real-world environments - delivering quality assurance protocols, technical documentation, and submission-ready analytics datasets - backed by contributions to open-source projects or scientific publications in healthcare AI.

Roche is an Equal Opportunity Employer. #J-18808-Ljbffr