Director of Algorithms Development

Другое

• Company - Who We Are? Company is a growing AI startup in the clinical trial space, leveraging AI, biomedical data, knowledge graphs, and real-world patient data to simulate and optimize clinical trials for pharmaceutical companies. Our platform helps customers simulate clinical trials, reduce development risk and cost, shorten timelines, and improve the probability of clinical trial success.
• About the Role Company’s core technology is built around simulation, prediction, and AI-driven clinical trial optimization. We develop machine learning systems that model patient outcomes, treatment effects, enrollment dynamics, and clinical trial success, leveraging large-scale real-world healthcare data, biomedical knowledge, and advanced machine learning techniques.
• We are looking for a Director of AI & Algorithms to lead the team responsible for developing the models and methodologies that power these capabilities.
• You will lead a team of researchers, data scientists, and algorithm developers working on clinical trial simulation, predictive modeling, foundation models, uncertainty quantification, and next-generation AI capabilities. You will be responsible for setting scientific direction, guiding major modeling decisions, establishing validation methodologies, and ensuring that Company continues to advance the state of the art in AI-driven clinical development.
• This role combines scientific leadership, people leadership, and technical depth. The ideal candidate has experience building and leading high-performing AI teams, developing machine learning products in production environments, and translating scientific innovation into measurable business impact.
• What Will You Do as Part of The Role?
• Lead and grow the AI & Algorithms team, including researchers, data scientists, and algorithm developers.
• Define the scientific and algorithmic roadmap for Company’s simulation, prediction, and AI platforms.
• Guide the development of foundation models, predictive models, simulation methodologies, and future AI-driven product capabilities.
• Establish validation methodologies, benchmarking standards, uncertainty quantification approaches, and model calibration strategies.
• Partner closely with Clinical Informatics, DataOps, MLOps, Product, and Engineering teams to translate scientific challenges into scalable solutions.
• Drive the evaluation and adoption of new machine learning methods, data representations, and modeling approaches.
• Review and guide major modeling, statistical, and methodological decisions across the organization.
• Own scientific publications, conference submissions, and external research collaborations related to Company’s core algorithms and simulation technologies.
• Represent Company’s scientific capabilities to customers, partners, investors, and the broader AI and healthcare communities.
• Mentor and develop senior technical talent while helping build a culture of scientific rigor, innovation, and execution.
• What does it require from you?
• Experience leading machine learning, AI, or applied research teams in production environments.
• Strong background in machine learning, statistics, predictive modeling, or related quantitative disciplines, both in industry and academia.
• Experience developing, evaluating, and deploying machine learning systems that drive real-world products or business outcomes.
• Strong understanding of model validation, experimental design, uncertainty quantification, and statistical evaluation methodologies.
• Experience translating ambiguous scientific or business problems into practical modeling solutions.
• Track record of recruiting, mentoring, and developing high-performing technical teams.
• Excellent communication skills and ability to collaborate across scientific, technical, and business functions.
• Ability to balance long-term scientific innovation with short-term product and business needs.
• Strong Advantages
• Experience developing foundation models, large-scale machine learning systems, or AI-first products.
• Experience working with healthcare, life sciences, biomedical, or real-world patient data.
• Track record of scientific publications, conference presentations, or external thought leadership.
• Experience developing simulation systems, causal inference methodologies, time-to-event models, or advanced predictive modeling systems.
• Experience in high-growth startup environments where both technical leadership and execution are required.
• Notes
• At Company, we believe in creating an inclusive and diverse work environment where everyone can thrive and contribute to our shared goals. We welcome applicants from all backgrounds and experiences.
• We mix remote and in-office work. Most of the team is in the office two days a week and works from home the remaining days.