Staff Data Scientist, AI/ML
New
Based in the United StatesFull-TimeStaff
Salary$170,000 – $248,000 (salary + equity)
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Job Details
- Experience
- 5+ years
- Required Skills
- PythonSQLMachine LearningPyTorchTensorflowData visualizationA/B testingDeep LearningLLM
Requirements
- 5+ years of professional experience in Data Science, Machine Learning Engineering, or related roles handling complex, high-volume datasets
- Strong foundation in statistical methods, including experimental design, probability, and exploratory data analysis
- Deep expertise in modern ML techniques, including deep learning architectures and LLM training/fine-tuning approaches (e.g., SFT, DPO, RFT)
- Proven experience building and deploying large-scale models using frameworks such as PyTorch or TensorFlow
- Advanced SQL skills with ability to write and optimize complex queries across relational data systems
- Strong Python proficiency, including object-oriented programming and production-grade ML/data science code development
- Experience with distributed data processing systems and scalable model training pipelines
- Excellent communication and storytelling skills, with ability to translate technical insights into actionable business recommendations
- Strong intellectual curiosity, adaptability, and passion for continuous learning in fast-evolving ML/AI fields
Responsibilities
- Leverage large-scale, complex healthcare datasets to build, tune, and evaluate machine learning models and AI-driven product features
- Design and run statistical experiments, including A/B testing, exploratory data analysis, and model performance evaluation frameworks
- Develop and fine-tune modern deep learning and LLM-based systems, including approaches such as supervised fine-tuning and preference optimization methods
- Build scalable ML pipelines using distributed computing frameworks and ensure models are production-ready and reliable
- Collaborate with product, engineering, and analytics teams to define data science initiatives from ingestion through deployment and insights generation
- Create clear, compelling data visualizations and narratives to communicate complex findings to technical and non-technical stakeholders
- Contribute to strategic direction for AI/ML initiatives, helping shape roadmap priorities and long-term data science vision
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