We Are Modernizing Medicine (WAMM) is seeking to transform the way medical practices operate and deliver care through innovative, specialty-specific cloud platforms, and the Data Scientist role is instrumental in designing and implementing advanced machine learning models to drive predictive analytics and improve healthcare outcomes.
Requirements
- PhD in Computer Science, Data Science, Electrical Engineering, Mathematics, Physics, or a related quantitative field
- Proven research excellence with 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 within a product or platform-focused environment, preferably in healthcare or similar data-rich domains
- Proficiency in Python and common machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch)
- Experience with MLOps tools and cloud-based ML environments such as AWS
- Knowledge of healthcare data formats (HL7, FHIR) and privacy standards (HIPAA) is a plus
- Strong understanding of statistical methods, experimental design, and data wrangling techniques
Responsibilities
- Design and develop advanced machine learning models for prediction, classification, personalization, and automation use cases
- Translate complex business problems into effective ML solutions, collaborating with stakeholders to identify opportunities for data-driven impact
- Build, evaluate, and optimize models using techniques such as supervised/unsupervised learning, time-series forecasting, NLP, and deep learning where applicable
- Manage the end-to-end lifecycle of ML models, including data exploration, feature engineering, deployment, monitoring, and retraining
- Lead cross-functional ML projects, working closely with product teams, data engineers, analysts, and software engineers
- Partner with data engineering teams to ensure the availability of high-quality, reliable data pipelines for analytics and ML tasks
- Contribute to the development of scalable ML infrastructure and tools to support experimentation and production deployment
Other
- PhD in Computer Science, Data Science, Electrical Engineering, Mathematics, Physics, or a related quantitative field
- United States: Medical, dental, and vision insurance, Health Savings Account contributions, 401(k) with company matching, generous paid time off and parental leave, company-paid life and disability benefits
- Equal employment opportunities to all applicants and employees regardless of race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or any other protected status
- Collaborate with various business units (product, marketing, operations) to validate insights and facilitate data-informed decisions
- Create visualizations, dashboards, and reports to communicate findings effectively to technical and non-technical audiences
