Data Scientist

Role 

As a Data Scientist at SmarterDx, you will contribute to training and improving machine learning models and ensuring their integration into our Smarter Revenue Platform. Your work will involve supporting the development, deployment, and improvement of machine learning models, ensuring they drive measurable business impact. 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.

SmarterDx builds clinical AI that empowers hospitals to analyze the complete record of every patient to fully capture the value of care delivered. Founded by physicians in 2020, its proprietary AI platform understands the nuances of clinical reasoning, enabling hospitals to true the patient record for every discharge. By doing so, hospitals can recover millions in earned revenue, enhance care quality metrics, and optimize healthcare operations. Become a Smartian and help optimize the way the healthcare system works for everyone. Learn more at smarterdx.com/careers.

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

What You’ll Do

• Support the development and refinement of modeling approaches in 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.
• Assist with deployment efforts, including testing model performance and integrating models into product workflows.
• Help improve shared modeling infrastructure by contributing to tools and utilities that support experimentation.
• 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.
• Help identify areas for improvement in existing models and share findings with the team.

What You Bring

• 1-3 years of experience in data science, machine learning, or a related field, preferably in a product-driven environment.
• Proficiency in Python and familiarity with machine learning frameworks such as PyTorch or scikit-learn.
• 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.
• Exposure to deploying machine learning models and optimizing their performance based on feedback.
• Strong collaboration skills and the ability to work across cross-functional teams including Engineering, Product, and Analytics.
• A problem-solving mindset with the ability to balance technical rigor with practical business impact.

Nice To Haves

• 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.
• Familiarity with cloud platforms (AWS, GCP, or Azure) and MLOps best practices.
• Previous experience working in a startup or high-growth environment.
• Knowledge of explainable AI techniques and model interpretability best practices.

Our Tech Stack

• Python
• SQL
• PyTorch
• Sagemaker
• Snowflake

Compensation 

• $140-170k base + equity incentives