Senior AI Data Scientist I

Exelixis; Alameda (CA); On-site; USD 143,500 - 203,000; Full time

Benefits offered by this job

401(k) with company contributions

Health, dental, vision

Life and disability insurance

Stock purchase options

Paid time off and holidays

Job summary

Exelixis is seeking a Senior AI Data Scientist I to develop, validate and productionize AI/ML models for clinical data. You will clean data from diverse sources, implement SDTM/ADaM standards, and build automated AI workflows for analysis and reporting.

The role requires strong Python/R skills, SQL proficiency, and experience with Databricks and AWS. Collaboration with clinical operations and data management is essential.

Qualifications

• Bachelor's degree or higher in quantitative field with multiple years of AI/ML experience.
• PhD/advanced degrees optional but impact varies by experience.

Responsibilities

• Build, train and validate ML models on clinical datasets.
• Perform data cleaning and standardization to SDTM/ADaM.
• Develop LLM-based workflows for automated reviews and queries.
• Create dashboards for clinical data review and study monitoring.
• Ensure QA, validation, and GxP compliance of outputs.

Skills

Python

R

SQL

NLP

LLM APIs

Databricks

AWS

Git/GitHub

BI tools (Tableau/Power BI)

CDISC (SDTM/ADaM)

Education

Bachelor's degree in Data Science/CS/Statistics or related field

Master's degree in Data Science/CS/Statistics or related field

Equivalent combination of education and experience

Tools

Databricks

AWS

Jira

GitHub

Tableau/Power BI

Job description

Summary / Job Purpose

The Senior AI Data Scientist I develops, trains and validates AI/ML models and analytics solutions that transform complex clinical datasets into analysis-ready deliverables supporting drug-development decisions. Leveraging statistical programming (R, Python, SQL) and machine-learning techniques, this role executes automated workflows, data quality assurance, and regulatory-compliant outputs within a GxP-governed clinical data pipeline. This position exists to advance the organization's AI/ML and data science capabilities across clinical development – collaborating with Statistical Programming, Clinical Data Management, and Clinical Operations to accelerate data‑driven insights, improve data infrastructure, and ensure the accuracy and reproducibility of analytical outputs that inform study‑level and portfolio‑level decisions.

Essential Duties / Responsibilities

• Build, train and validate machine-learning models (supervised and unsupervised) on clinical datasets under the direction of senior data scientists, ensuring model performance meets predefined acceptance criteria.
• Execute data cleaning, transformation, and standardization tasks across clinical datasets from EDC, vendor and real-world data sources, aligning outputs with CDISC (SDTM/ADaM) standards.
• Develop and maintain LLM‑based and generative AI‑workflows for automated TLF review and ad‑hoc analytical queries, applying human‑in‑the‑loop validation to ensure output reliability.
• Create interactive dashboards and visualizations that support clinical data review, study‑health monitoring, and decision‑making across cross‑functional stakeholders.
• Execute data validation checks and quality‑assurance procedures to ensure accuracy, reproducibility and compliance of analytical outputs with GxP requirements.
• Support the development and maintenance of data pipelines on Databricks and AWS cloud infrastructure, applying version control (Git/GitHub) and CI/CD best practices.
• Collaborate with Statistical Programming, Clinical Data Management, and Clinical Operations to deliver AI/ML project milestones and address study‑level data needs.
• Prepare and maintain documentation of model development, data transformation, and validation activities consistent with SOPs and work instructions.
• Drive external scientific visibility and publication objectives by contributing to manuscripts, conference presentations and white papers that showcase clinical AI/data science innovations.
• Pursue continuous professional development in emerging AI/ML techniques, cloud‑based data platforms, and clinical data science methodologies to advance team capabilities.
• Perform other duties as assigned.
• Comply with all policies and standards.

Supervisory Responsibilities

• None

Education / Experience / Knowledge / Skills & Abilities

Education

• Bachelor's degree in Data Science, Computer Science, Statistics, Biostatistics, Bioinformatics, or a related quantitative field and a minimum of 7 years of experience; or,
• Master's degree in Data Science, Computer Science, Statistics, Biostatistics, Bioinformatics, or a related quantitative field and a minimum of 5 years of experience; or,
• Equivalent combination of education and experience.

Experience

• With PhD: No prior experience applying AI/ML methods to structured or unstructured data.
• With Master's degree: A minimum of 1 year of experience applying AI/ML methods to structured or unstructured data.
• With Bachelor's degree: A minimum of 3 years of experience applying AI/ML methods to structured or unstructured data.
• Without degree: A minimum of 7 years of relevant professional experience, including demonstrated application of AI/ML methods to structured or unstructured data.

Required Skills & Abilities

• Intermediate proficiency in Python (Pandas, NumPy, scikit-learn) for data manipulation and model prototyping.
• Intermediate proficiency in R for statistical analysis and visualization.
• Basic proficiency in SQL for data querying and transformation.
• Intermediate understanding of supervised and unsupervised learning fundamentals, including model evaluation.
• Basic familiarity with NLP, text mining and/or time series analysis techniques.
• Basic familiarity with LLM APIs and prompt engineering concepts.
• Basic knowledge of Databricks notebooks and Delta Lake concepts.
• Basic familiarity with AWS cloud services (S3, Lambda, Glue).
• Basic understanding of data pipeline concepts and data integration fundamentals.
• Intermediate proficiency with version control (Git/GitHub) and project tracking tools (Jira).
• Intermediate proficiency with BI platforms including Spotfire, Tableau and/or Power BI.
• Basic understanding of the clinical development process and regulatory requirements (ICH, GxP).
• Basic familiarity with CDISC data standards (SDTM, ADaM) concepts.
• Ability to communicate technical concepts clearly to diverse audiences.
• Strong collaboration and teamwork skills in a cross‑functional environment.
• Attention to detail and organizational skills.
• #LI-JP1

Compensation and Benefits

Base pay range: $143,500 – $203,000 annually, adjusted by geographic region. In addition to base salary, benefits include 401(k) with company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts. Employees may receive a discretionary annual bonus, stock purchase options, and long‑term incentives. Paid time off includes 15 accrued vacation days in the first year, 17 paid holidays, and up to 10 sick days annually.

Work Conditions

Our office is a modern space that fosters collaboration and creativity. Teams work closely together, sharing ideas and solutions in a supportive atmosphere. We provide all necessary equipment, including dual monitors and ergonomic chairs, to ensure a comfortable workspace.

Disclaimer

The preceding job description has been designed to indicate the general nature and level of work performed by employees within this classification. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications required of employees assigned to the job.

Equal Opportunity Employer

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class.