
About Tempus
Transforming healthcare with data-driven insights
Key Highlights
- Largest library of clinical and molecular data in the world
- Headquartered in Chicago, Illinois
- Over $1 billion raised from top-tier investors
- 1,000+ employees dedicated to healthcare technology
Tempus, headquartered in Chicago, Illinois, is a technology company that has developed the largest library of clinical and molecular data, focusing on oncology. With over 1,000 employees, Tempus partners with leading healthcare institutions to provide data-driven insights and personalized treatment ...
🎁 Benefits
Tempus offers competitive salaries, equity options, generous PTO, flexible remote work policies, and comprehensive health benefits, including parental...
🌟 Culture
Tempus fosters a culture of innovation and collaboration, emphasizing data-driven decision-making and a commitment to improving patient outcomes throu...
Skills & Technologies
Overview
Tempus is hiring an Associate Principal/Director of Data Science to develop predictive models for oncology therapies. You'll leverage machine learning and generative AI to advance precision medicine. This role requires strong expertise in applied machine learning and experience with real-world data.
Job Description
Who you are
You have a strong background in data science with a focus on machine learning and generative AI — your experience includes applying advanced algorithms to real-world datasets, particularly in healthcare. You possess expertise in computational biology and biostatistics, enabling you to analyze complex biological data effectively. Your ability to communicate complex findings to diverse stakeholders sets you apart, ensuring that insights are actionable and impactful. You are familiar with large multimodal datasets and understand the nuances of genomic and clinical data, which is crucial for developing predictive models in oncology.
You thrive in innovative environments where you can leverage cutting-edge technology to make a difference in clinical care. Your passion for precision medicine drives you to explore new methodologies and tools that can enhance patient outcomes. You are adept at working collaboratively with cross-functional teams, including engineers and healthcare professionals, to translate data insights into practical applications. You are committed to ethical standards in handling sensitive health information, ensuring compliance with legal requirements.
What you'll do
In this role, you will lead the development of predictive models that guide optimal therapy decisions in oncology — your work will directly impact patient care by providing real-time insights to physicians. You will build a generative AI-driven discovery platform that utilizes Tempus' extensive real-world database, fusing features from various data modalities to uncover predictive opportunities. Your responsibilities will include designing and implementing complex algorithms, conducting experiments to validate model performance, and iterating on your findings to enhance accuracy and reliability.
You will also mentor junior data scientists, fostering a culture of learning and innovation within the team. Collaborating closely with stakeholders, you will communicate your findings and recommendations effectively, ensuring that the insights derived from data are understood and utilized in clinical settings. Your role will involve staying abreast of the latest advancements in AI and machine learning, applying these insights to improve the predictive capabilities of Tempus' platform.
What we offer
Tempus provides a dynamic work environment where you can make a significant impact on the healthcare industry. You will have access to one of the largest multimodal patient datasets, offering unique opportunities for research and innovation. The company values collaboration and encourages you to bring your ideas to the table, contributing to the advancement of precision medicine. We offer competitive compensation and benefits, along with opportunities for professional growth and development in a rapidly evolving field.
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