Sr Data Scientist

Accountabilities:

• Optimize, fine-tune, and evaluate large language models (LLMs) and machine learning systems using proprietary clinical and operational datasets

• Assess model performance across key metrics such as precision, recall, relevance, and domain-specific benchmarks, identifying areas for improvement

• Design and implement retrieval-augmented generation (RAG) systems and other AI-driven solutions to enhance platform capabilities

• Collaborate with data engineering, product, and domain experts to translate clinical research challenges into scalable ML and AI solutions

• Build and maintain efficient ML pipelines using tools such as Databricks, MLflow, and Delta Lake for training, evaluation, and deployment

• Evaluate and select appropriate models, including open-source and proprietary options, based on performance and domain fit

• Ensure model interpretability, fairness, and compliance through bias analysis, validation, and governance documentation

• Contribute to reusable frameworks for model training, fine-tuning, and monitoring within the broader AI ecosystem

• Stay current with advancements in LLMs, retrieval systems, and multimodal AI, applying innovations to improve scalability and efficiency

Requirements:

• Master’s degree in Machine Learning, Computer Science, or a related quantitative field, or equivalent professional experience

• 5+ years of hands-on experience building, training, and fine-tuning machine learning or large language models

• Strong programming skills in Python with experience using frameworks such as PyTorch

• Proven experience working with Databricks for data engineering, ML workflows, and model deployment

• Deep understanding of the end-to-end machine learning lifecycle

• Hands-on experience with embeddings and retrieval-augmented generation (RAG) systems

• Strong analytical mindset with the ability to evaluate model performance and translate results into improvements

• Ability to work collaboratively across technical and domain teams in a highly cross-functional environment

• Preferred: PhD in a relevant field, experience with causal inference or graph-based reasoning, and familiarity with biomedical or clinical data contexts

• Strong curiosity for applied AI and a mindset focused on continuous experimentation and improvement

Benefits:

• Competitive base salary ranging from $91,524 to $167,794 depending on experience and location

• Eligibility for performance-based variable bonus

• Comprehensive health coverage and employee benefits package

• Paid holidays and flexible remote work across the United States

• Opportunity to work on impactful AI applications in clinical research and healthcare innovation

• Exposure to advanced LLM, RAG, and production-scale machine learning systems

• Inclusive, collaborative, and mission-driven work environment focused on improving global health outcomes

How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
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