Senior Data Scientist

As a Senior Data Scientist at SmarterDx, you will play a pivotal role in training cutting-edge machine learning models and ensuring their strategic integration into our Clinical AI Platform. Your work will focus on maximizing the business impact of deployed models by optimizing business logic, refining decision frameworks, and accelerating the end-to-end process of model development and deployment. You will collaborate closely with cross-functional teams to enhance our models’ clinical intelligence and delight our customers. This is a high-impact role ideal for someone who thrives in a fast-paced environment and is eager to see their work translate into tangible business outcomes.

**This role is fully remote within the US**

• →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.

• 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.

• Experience in healthcare or revenue cycle management.
• Familiarity working with large-scale data warehouses such as Snowflake.
• Experience building internal tools or infrastructure to support machine learning experimentation and deployment.
• Previous experience working in a startup or high-growth environment.
• Knowledge of explainable AI techniques and model interpretability best practices.
• Experience developing products leveraging Large Language Models (LLMs).

• Python
• SQL
• PyTorch
• Sagemaker
• Snowflake