Clinical Data Scientist

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Requirements:

• Experience working with data at scale, performing cleaning, feature extraction and model training, testing and validation.
• Demonstrable knowledge of generative AI, prompt engineering, and output validation/sanitization techniques.
• Experience working directly with product teams, especially in clinical or youth-focused healthcare environments.
• Foundational expertise in biostatistics, including study design, hypothesis testing, and interpreting clinical data.
• Demonstrated ability to analyze and validate complex datasets with scientific rigor.
• Proven experience building research pipelines that prioritize transparency and reproducibility.
• A collaborative mindset and excellent communication skills to bridge data science, engineering, and product.

Responsibilities:

• Develop and validate generative AI models for wellness initiatives, ensuring clinical relevance and scientific rigor.
• Act as the point person for data engineering and product teams, ensuring seamless integration of models into products and workflows.
• Serve as the primary analyst for scientific outputs, contributing to data-driven insights and analyses for internal and external audiences.
• Build and refine research pipelines that adhere to rigorous, transparent, and reproducible practices, ensuring consistency across analyses.
• Collaborate with cross-functional teams to design and execute data analyses for clinical and product-related research.
• Contribute to the writing and publication of peer-reviewed manuscripts by providing biostatistical expertise and data analysis.