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Data Scientist - Research Sovereign AIMayo Foundation for Medical Education and Research • Rochester, New York, United States
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Data Scientist - Research Sovereign AI

Mayo Foundation for Medical Education and Research
  • US
    Rochester, New York, United States
  • US
    Rochester, New York, United States
Jetzt Bewerben

Über

Benefits Highlights
Medical: Multiple plan options.
Dental: Delta Dental or reimbursement account for flexible coverage.
Vision: Affordable plan with national network.
Pre-Tax Savings: HSA and FSAs for eligible expenses.
Retirement: Competitive retirement package to secure your future.
Responsibilities The Data Scientist for Foundational Model Science is the senior technical leader, and the lead scientist responsible for designing, training, and governing Mayo’s multimodal foundational model. This model forms the core intelligence layer used by clinical departments, researchers, agentic workflows, and sovereign AI collaborations. The individual will work as a hands‑on architect, model‑builder, and researcher while acting as a player–coach, guiding strategy and building a future team.
Scientific & Technical Leadership
Design multimodal foundational model architectures integrating signals from imaging, text, waveforms, structured data, graph representations, and temporal embeddings.
Develop fusion, alignment, and cross‑modal reasoning mechanisms (early fusion, late fusion, token‑level fusion, hybrid models).
Define and implement methods for grounded clinical reasoning, retrieval‑augmented inference, graph‑augmented attention, and chain‑of‑thought verification.
Establish protocols for model lifecycle governance, safe update cycles, drift‑aware re‑training, and provenance tracking.
Hands‑On Modeling & Training
Train large‑scale deep learning models, including multimodal architectures and domain‑specific transformer‑based systems, on real clinical datasets.
Fine‑tune and adapt large language models (LLMs) for clinical reasoning, summarization, question answering, agentic behavior, and instruction‑following tasks.
Build retrieval‑augmented pipelines using embeddings, vector stores, graph traversal, and clinically grounded context construction.
Develop evaluation methods for reasoning quality, temporal prediction accuracy, multimodal synergy, ablation‑based robustness, and counterfactual behavior.
Create reference‑grounded training datasets, structured reasoning tasks, and multimodal benchmarks to evaluate model performance.
Conduct hands‑on experimentation with optimization strategies, large‑scale distributed training, model quantization, and inference acceleration.
Implement uncertainty modeling, selective prediction, abstention mechanisms, and clinically meaningful risk thresholds.
Build interpretable reasoning pathways, cross‑modal attribution maps, and reference‑grounded explanations.
Cross‑Functional Collaboration
Work closely with the Representation team to ensure representation‑model alignment.
Partner with clinical SMEs to encode domain reasoning into reinforcement learning, preference optimization, or rule‑guided behaviors.
Team Leadership
Serve as the future founding technical lead of the Foundational Model Science Program.
Mentor scientists and engineers and eventually build a specialty modeling team.
Qualifications Required
PhD in Machine Learning, Computer Science, Applied Mathematics, or related discipline with at least four years of informatics, Artificial Intelligence, data science and/or machine learning.
Experience with generative modeling, reasoning models, or multimodal foundation models.
Expertise in alignment methods (contrastive learning, RLHF/RLCS, preference optimization).
Experience with distributed training, and large‑scale compute.
Preferred
Experience with clinical or EMR data across multiple modalities.
7+ years experience training deep learning models, including transformers or multimodal architectures.
Experience defining evaluation frameworks for reasoning, multimodal synergy, reliability, or fairness.
Publications in multimodal learning, foundation models, or reasoning architectures.
Compensation Education, experience and tenure may be considered along with internal equity when job offers are extended. $165,276 - 247,998 annually.
Exemption Status Exempt
Benefits Eligible Yes
Schedule Full Time
Hours/Pay Period 80
Schedule Details Monday – Friday. Regular day hours.
Weekend Schedule none expected
International Assignment No
Equal Opportunity All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, protected veteran status or disability status. Mayo Clinic participates in E‑Verify and may provide the Social Security Administration and, if necessary, the Department of Homeland Security with information from each new employee's Form I‑9 to confirm work authorization.
Recruiter Jill Squier
#J-18808-Ljbffr
  • Rochester, New York, United States

Sprachkenntnisse

  • English
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