Job Title: Principal Data Scientist Contract: 12-month contract with potential for extension/conversion Fully Remote, must be comfortable working EST Hours Pay: Bid rate position! Manager is open on pay rate at long as candidate meets qualifications PLEASE NOTE THE QUALIFICATIONS: • PhD or Master's degree in a quantitative field (e.g., Computer Science, Statistics, Biomedical Informatics, Engineering, Physics). • MUST HAVE: Experience with Disease onset or prognostic modeling • Demonstrated expertise in machine learning algorithms and deep learning architectures, including strong practical experience with transformer models (e.g., BERT). • Proficiency in programming languages such as Python or R, and experience with relevant data science libraries (e.g., scikit-learn, TensorFlow, PyTorch, XGBoost). • Experience working with large-scale, real-world healthcare datasets such as claims data, electronic health records (EHR), or clinical trial data. Job Description: • We are seeking an experienced and visionary Principal Data Scientist to lead our efforts in developing advanced predictive models and AI solutions for healthcare. • E.D.G.E. Team (Emerging Disruptive Growth Exploration) conducts cutting-edge research in health care and incubates data-driven digital and non-digital solutions which aim to improve a person’s health outcomes, the lives and ability for families to support and care for their loved ones, clinicians’ experience, and to reduce health care costs. • The ideal candidate will possess a deep understanding of machine learning methodologies, a proven track record of delivering impactful data-driven solutions in a real-world setting, and the ability to drive innovation across diverse therapeutic areas. • Lead the design, development, and deployment of cutting-edge predictive models using various machine learning and AI techniques, including tree-based models (e.g., XGBoost) and transformer-based architectures (e.g., BERT), for early disease detection and proactive interventions. • Drive the strategic direction of data science initiatives across multiple therapy areas, identifying opportunities to leverage real-world data (e.g., open claims data, EHR) for improved patient outcomes and drug development, including the use of federated analytics and federatML. • Provide technical leadership and mentorship to a team of data scientists, fostering a culture of innovation, rigorous experimentation, and best practices in MLOps. • Evaluate and select appropriate modeling techniques and performance metrics (e.g., Precision, Recall, Bayes factor, NNT) based on specific problem statements and business objectives. • Collaborate closely with cross-functional teams including business owners, payers, clinicians, epidemiologists, statisticians, and IT to translate complex business problems into tractable data science solutions for deployment in real world. • Stay abreast of the latest advancements in machine learning, deep learning, and AI, and proactively integrate Client approaches into our predictive modeling capabilities. • Communicate complex analytical findings and their implications clearly and concisely to both technical and non-technical audiences.