Passionate about precision medicine and advancing the healthcare industry?

Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus’s proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients at the right time.

This role is for an experienced leader in the application of machine learning and neural models to electronic health records for clinical decision support and research.

What You Will Do:

• Lead and grow the EHR AI team, including hiring, managing, and mentoring team members.
• Design and prototype novel analysis tools and algorithms for electronic phenotyping on both structured and unstructured EHR data.
• Research, develop, train, test, deploy, monitor, and improve machine learning models for phenotyping, clinical prediction, information extraction, decision support, and precision medicine.
• Collaborate with stakeholders, product, science, engineering, and business development teams to build the most advanced solutions in precision medicine.
• Perform user-centered design with customers and stakeholders to create the highest impact machine learning systems.
• Interrogate analytical results for robustness, validity, and out-of-sample stability.
• Document, summarize, and present your findings to peers and stakeholders.
• Guide the team’s direction and technical roadmap, while also being hands-on and a strong individual contributor yourself.
• Provide technical leadership and expertise across multiple projects.

Required Qualifications:

• PhD degree in a quantitative discipline such as computer science, machine learning, statistics, natural language processing, computational biology, bioinformatics, applied mathematics, or physics.
• 5+ years of relevant industry experience.
• Proven ability to lead and manage small- to medium-sized teams.
• Expert-level knowledge of a variety of unsupervised, semi-supervised, and supervised deep learning methods for phenotyping, clinical prediction, and representation learning.
• Highest standard of scientific rigor and ability to balance high academic quality against fast-paced product requirements.
• Outstanding analytical and problem-solving skills.
• Excellent written and verbal communication skills.
• Strong individual track record and hands-on mentality.
• Strong technical proficiency in a range of tools such as Python, PyTorch, TensorFlow, NumPy, SciPy, Pandas, scikit-learn, and Linux.
• Strong understanding of software best practices to serve as role model for the team and maintain a high level of quality and scalability on the technical as well as the scientific side.
• Ability to thrive in a fast-paced environment and willingness to shift priorities seamlessly.
• Experience with communicating insights and presenting concepts to diverse audiences.
• Team player mindset and ability to work in an interdisciplinary team.
• Goal orientation, self motivation, and drive to make a positive impact in healthcare.

Preferred Qualifications:

• Experience in a late-stage startup environment.
• Experience working with PHI or PII and familiarity with human/machine hybrid data structuring workflows.
• Strong peer-reviewed publication record.
• Successful history of building and leading a highly functional team from the ground up.
• Experience with sensitive patient data and working under HIPAA regulations.
• Ability to attract high potential junior as well as senior talent.

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