Jobs Companies Exelixis Senior AI Data Scientist I

Sobre esta vaga de Senior AI Data Scientist I na Exelixis

Exelixis · Presencial · Alameda, CA

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.
  • Performs other duties as assigned
  • Complies 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 one (1) year of experience applying AI/ML methods to structured or unstructured data.
  • With Bachelor's degree: A minimum of three (3) years of experience applying AI/ML methods to structured or unstructured data.
  • Without degree: A minimum of seven (7) years of relevant professional experience, including demonstrated application of AI/ML methods to structured or unstructured data.


Knowledge, Skills and Abilities

Required:

  • 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

Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The base pay range for this position is $143,500 - $203,000 annually. The base pay range may take into account the candidate’s geographic region, which will adjust the pay depending on the specific work location. The base pay offered will take into account the candidate’s geographic region, job-related knowledge, skills, experience and internal equity, among other factors.

In addition to the base salary, as part of our Total Rewards program, Exelixis offers comprehensive employee benefits package, including a 401k plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts. Employees are also eligible for a discretionary annual bonus program, or if field sales staff, a sales-based incentive plan. Exelixis also offers employees the opportunity to purchase company stock, and receive long-term incentives, 15 accrued vacation days in their first year, 17 paid holidays including a company-wide winter shutdown in December, and up to 10 sick days throughout the calendar year.


If you have a disability and need an accommodation in relation to the application and/or recruitment process, please email us at: [email protected].


WORKING 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.


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.

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Como este salário de Data Scientist se compara

Esta vaga paga $173,250/yrem linha com da faixa típica para vagas de Data Scientist.

$101,000 a mediana $170,500 $259,449

Faixa típica $130,500–$216,263/yr, com base em 1,297 vagas de Data Scientist comparáveis na JobsRadar (pagamento anualizado em USD). Ver insights salariais de Data Scientist →

Sobre a Exelixis

Every Exelixis employee is united in an ambitious cause: to launch innovative medicines that give patients and their families hope for the future. In this pursuit, we know our employees are our most valuable asset. After operating in the challenging biotech sector for 25 years, we have a proven track record of resiliency in the face of adversity. The success of our lead product has provided a solid commercial foundation allowing us to reinvigorate our research efforts, and grow our team in areas such as Drug Discovery, Clinical Development and Commercial. As we expand our global partnerships and further reinvest in R&D to help us discover the next breakthrough for difficult-to-treat cancers,

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