We Are Modernizing Medicine (ModMed) is seeking Data Scientists to drive data and machine learning initiatives that fuel innovation and business growth by solving complex problems using data and building production-grade ML systems.
Requirements
- Strong proficiency in Python and common ML libraries.
- Experience with MLOps tools and cloud-based ML environments such as AWS.
- Solid understanding of statistical methods, experimental design, and data wrangling.
- Proven track record of research excellence demonstrated by publications in top ML/AI conferences (e.g., NeurIPS, ICML, ICLR, ACL, CVPR, AAAI, KDD) or journals.
- Hands-on experience in data science or machine learning in a product or platform-focused environment preferably in healthcare or similar data-rich domain.
- Experience working with healthcare data formats (HL7, FHIR) and privacy standards (HIPAA) is a plus.
- Familiarity with SQL, Spark, and distributed data systems is a plus.
Responsibilities
- Design and implement advanced machine learning models and algorithms for prediction, classification, personalization, and automation use cases.
- Translate business problems into machine learning solutions, working closely with stakeholders to identify opportunities for data-driven impact.
- Build and evaluate models using techniques such as supervised/unsupervised learning, time-series forecasting, NLP, and deep learning where applicable.
- Own the end-to-end lifecycle of machine learning models, from data exploration and feature engineering to deployment, monitoring, and retraining.
- Lead cross-functional ML projects, collaborating with product managers, data engineers, analysts, and software engineers.
- Partner with data engineering teams to ensure robust data pipelines and access to high-quality, clean, and reliable data for analytics and ML.
- Contribute to the design and development of scalable ML infrastructure and tools to support training, experimentation, and production deployment.
Other
- PhD in Computer Science, Data Science, Electrical Engineering, Mathematics, Physics, or a related quantitative field.
- Work with stakeholders across the business (product, marketing, operations) to validate findings and support data-informed decisions.
- Develop visualizations, dashboards, and reports to communicate results to technical and non-technical audiences.
- Analyze large datasets to generate actionable insights, uncover trends, and support strategic decisions.
