Head of Knowledge Technologies
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' 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 field of NLP and Machine Learning who is an expert in applying state of the art techniques for clinical data structuring, information extraction, and event prediction. The role will report directly to the Chief of AI.
What You Will Do:
- Lead and further grow the Tempus Knowledge Technologies division, managing and mentoring a group of high caliber teams and individual contributors.
- Guide the team's direction and technical roadmap, while also being hands-on and a strong individual contributor yourself.
- Contribute to setting the company’s strategy for developing and applying Machine Learning tools for increasing the value and usefulness of Tempus’ clinical records.
- Collaborate closely with other functional leads as well as adjacent departments including engineering, product, science and business development.
- Manage internal and external stakeholders and downstream customers of your team’s work.
- Provide technical leadership & expertise across a multitude of projects.
Required Qualifications:
- PhD degree in a quantitative discipline (e.g. NLP, computer science, machine learning, statistics, applied mathematics, physics, or similar).
- 8+ years of relevant industry experience.
- Proven ability to lead a team of teams, and foster a culture of strong cross-team collaboration while furthering strong autonomy and focus of sub-teams.
- Expert level knowledge of modern NLP methods for information extraction, topic modeling, parsing, and relationship extraction, Natural Language Understanding, Knowledge Graphs, and representations for modern machine learning.
- Expert level knowledge of language models (LSTMs, n-grams, etc), ontologies and knowledge databases, and/or large database contextual search.
- Highest standard of scientific rigor, and an acute awareness to balance high academic quality versus fast-paced product requirements.
- Outstanding analytical and problem solving skills.
- Strong individual track record and hands-on mentality.
- Strong technical proficiency in a range of tools such as Python, SciPy, AWS, SageMaker, TensorFlow, PyTorch, etc.
- Strong understanding of software best practices to serve as role model for their team and maintain a high level of quality and scalability on the technical as well as scientific side.
- Thrive in a fast-paced environment and willing 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, familiarity with human/machine hybrid data structuring workflows.
- Strong peer-reviewed publication record.
- 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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