Lead Data Scientist

• “Applicants must be authorized to work in the U.S.”
• “We are unable to sponsor work visas.”

hands-on experience for disease onset or prognostic modelling

We are seeking an experienced and visionary Principal Data Scientist to lead our efforts in developing advanced predictive models and AI solutions for healthcare. 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.

Main responsibilities. The overall purpose and main responsibilities are listed below:

o 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.

o 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.

o Provide technical leadership and mentorship to a team of data scientists, fostering a culture of innovation, rigorous experimentation, and best practices in MLOps.

o Evaluate and select appropriate modeling techniques and performance metrics (e.g., Precision, Recall, Bayes factor, NNT) based on specific problem statements and business objectives.

o 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.

o Stay abreast of the latest advancements in machine learning, deep learning, and AI, and proactively integrate Client approaches into our predictive modeling capabilities.

o Communicate complex analytical findings and their implications clearly and concisely to both technical and non-technical audiences.

About you

• PhD or Master's degree in a quantitative field (e.g., Computer Science, Statistics, Biomedical Informatics, Engineering, Physics).

• 8+ years of progressive experience in data science, with a significant portion focused on predictive modeling and advanced analytics in healthcare or life sciences.

• 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.

• Strong understanding of statistical concepts and experimental design.

• Proven ability to lead complex data science projects from conception to deployment, with a focus on delivering measurable business impact.

• Excellent communication, interpersonal, and leadership skills, with the ability to influence and collaborate effectively across all levels of the organization.