Senior Data Scientist - Clinical AI Platform
S
SmarterDxHealthcare AI
USFull-TimeSenior
Salary200000 - 220000 USD per year
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Job Details
- Experience
- 3+ years
- Required Skills
- AWSPythonSQLGCPPyTorchAzureTensorflow
Requirements
- 3+ years of experience in data science, machine learning, or a related field, preferably in a product-driven environment.
- Strong proficiency in Python and hands-on experience with deep learning frameworks (PyTorch, TensorFlow).
- Deep understanding of statistical modeling, optimization techniques, and data analysis.
- Experience working with structured and text data, including feature engineering and data preprocessing.
- Ability to translate business objectives into data science problems and effectively communicate results to stakeholders.
- Experience deploying machine learning models into production and optimizing model performance based on real-world feedback.
- Strong collaboration skills and the ability to work across cross-functional teams including Engineering, Product, and Analytics.
- Familiarity with cloud platforms (AWS, GCP, or Azure) and MLOps best practices.
- A problem-solving mindset with the ability to balance technical rigor with practical business impact.
Responsibilities
- Develop and refine modeling approaches in close collaboration with the Machine Learning Research team, iterating on experiments to improve model performance.
- Execute rapid experimentation cycles, documenting learnings and identifying promising avenues for further development.
- Support deployment efforts by creating standardized model endpoints and interfaces for seamless integration with product workflows.
- Contribute to shared modeling infrastructure, building tools and utilities that accelerate experimentation and standardize workflows across teams.
- Collaborate with Engineering, Analytics, and Product teams to integrate machine learning models into product workflows, ensuring they drive measurable business KPIs.
- Adapt and enhance existing modeling approaches to drive impact in new product areas.
- Identify product needs and communicate them effectively across the Data Science and Machine Learning Research Science teams.
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