Exel
Senior AI Data Scientist I
Alameda, CA · Senior
Stay score
odds of building a lasting career here
Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
Personalize to your clock →H-1B wage level
the lottery is wage-weighted — each level is one more entry
$31,012 more — $174,512 — moves this role to Level III and 3 lottery entries. That figure is inside the range the employer already advertised.
Based on the DOL prevailing wage for this occupation and worksite, a base salary of $174,512 would place this position at wage Level III. That figure is within the posted range, and I'd like to target it. This role classifies under "Data Scientists" for prevailing-wage purposes.
DOL prevailing wage, 2026-27 wage year · Data Scientists (15-2051) · San Francisco-Oakland-Fremont, CA. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.
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Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.
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About the role
- 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.
- 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.
Responsibilities
- 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.
- 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.
- Performs other duties as assigned
Requirements
- 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.
- Bachelor's degree in Data Science, Computer Science, Statistics, Biostatistics, Bioinformatics, or a related quantitative field and a minimum of 7 years of experience
- Master's degree in Data Science, Computer Science, Statistics, Biostatistics, Bioinformatics, or a related quantitative field and a minimum of 5 years of experience
- 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.
Skills
- Equivalent combination of education and experience.
- 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.
Compensation
- 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.
Benefits
- 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.
- Create interactive dashboards and visualizations that support clinical data review, study-health monitoring, and decision-making across cross-functional stakeholders.
This listing is sourced directly from Exel's careers page and normalized into a canonical job model.