Sr Scientist II, Computational Discovery Science
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What you'll do
- Utilize novel analytical methods applied to multi-modal data—such as genomic, imaging, and clinical data—to identify targets in patient sub-populations.
- Apply in silico methodologies to Tempus Real-World Data (RWD) to identify molecular, biological, and clinical patterns associated with specific patient populations.
- Leverage multimodal data to compress complex data into joint embeddings, enabling robust clustering of patients and the identification of novel molecular subtypes.
- Utilize the LLM-orchestrated Tempus Loop Agent architecture to autonomously prioritize
- In partnership with Tempus’ modeling lab, use data from CRISPR and cell perturbation experiments in patient-derived organoids to identify and validate novel targets.
- Independently execute complex translational or real-world evidence research projects integrating molecular and clinical data from the Tempus multimodal data platform.
- Work closely with cross-functional teams across R&D and the broader Tempus organization, including product engineering, clinical genomics labs, data science, and medical teams.
- Communicate scientific and technical plans and outcomes to a cross-functional group of project and senior leadership stakeholders, both internal and external partners.
- Present scientific findings clearly and meaningfully to diverse sets of external stakeholders and non-technical audiences.
- Author abstracts, posters, and peer-reviewed publications to illustrate the value of multimodal analysis and AI in drug discovery.
What they're looking for
- Education: PhD in a quantitative discipline (e.g., Bioinformatics, Computational Biology, Data Science) or Life Sciences with a strong computational publication record.
- Experience: PhD with 4+ years of work experience leveraging genomic and multimodal data with machine learning approaches to address questions in complex diseases, especially cancer.
- Technical/Scientific Skills: Proficient in R, Python, and SQL. Strong understanding of Cancer, Genomics, and/or Immunology. Extensive prior experience analyzing genomic data and running statistical/machine learning models .
- Communication Skills: Excellent written and verbal communication skills, with the ability to present complex information clearly and persuasively to diverse audiences.
- Leadership Skills: Multidisciplinary project team leadership experience and a demonstrated ability to lead complex projects.
Nice to have
- Familiarity with the use of patient-derived organoid (PDO) models for target identification and validation, biomarker discovery, and identifying a drug’s mechanism of action (MOA) or preclinical proof-of-concept (POC).
- Experience with early-stage drug development, including target discovery and biomarker identification.
- Experience analyzing single-cell RNA sequencing and spatial transcriptomics.
- Proficient in computational biology packages and environments including Pandas, NumPy, SciPy, Scikit-learn, Jupyter Notebooks, RStudio, tidyverse, ggplot, Git, Docker, and AWS.
- Experience with R package development.
- Comfort in a client-facing role with prior consulting and/or client-facing experience.
- Ability to thrive in a fast-paced environment and willingness to shift priorities seamlessly.
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
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.
We are seeking a motivated and talented Senior Scientist II to join the Computational Discovery Science team. This scientist will contribute to a team focused on identifying novel targets for cancer therapeutics by developing and applying computational methods for drug discovery. You will leverage Tempus’ large clinico-genomic database alongside functional and molecular assays applied to patient-derived organoids (PDOs). This role demands a blend of creative and strategic thinking, leadership skills, and a passion for groundbreaking research. This is a highly collaborative role, requiring close partnership with AI/ML scientists, as well as computational and modeling lab biologists. You will also be client-facing, responsible for effectively communicating complex results to a diverse audience, including life science pharma and biotech partners.
Responsibilities:
Scientific & Computational Strategy:
● Utilize novel analytical methods applied to multi-modal data—such as genomic, imaging, and clinical data—to identify targets in patient sub-populations.
● Apply in silico methodologies to Tempus Real-World Data (RWD) to identify molecular, biological, and clinical patterns associated with specific patient populations.
● Leverage multimodal data to compress complex data into joint embeddings, enabling robust clustering of patients and the identification of novel molecular subtypes.
● Utilize the LLM-orchestrated Tempus Loop Agent architecture to autonomously prioritize ● In partnership with Tempus’ modeling lab, use data from CRISPR and cell perturbation experiments in patient-derived organoids to identify and validate novel targets.
Leadership & Independent Contribution:
● Independently execute complex translational or real-world evidence research projects integrating molecular and clinical data from the Tempus multimodal data platform.
● Work closely with cross-functional teams across R&D and the broader Tempus organization, including product engineering, clinical genomics labs, data science, and medical teams.
Scientific Communication:
● Communicate scientific and technical plans and outcomes to a cross-functional group of project and senior leadership stakeholders, both internal and external partners.
● Present scientific findings clearly and meaningfully to diverse sets of external stakeholders and non-technical audiences.
● Author abstracts, posters, and peer-reviewed publications to illustrate the value of multimodal analysis and AI in drug discovery.
Qualifications:
● Education: PhD in a quantitative discipline (e.g., Bioinformatics, Computational Biology, Data Science) or Life Sciences with a strong computational publication record.
● Experience: PhD with 4+ years of work experience leveraging genomic and multimodal data with machine learning approaches to address questions in complex diseases, especially cancer.
● Technical/Scientific Skills: Proficient in R, Python, and SQL. Strong understanding of Cancer, Genomics, and/or Immunology. Extensive prior experience analyzing genomic data and running statistical/machine learning models .
● Communication Skills: Excellent written and verbal communication skills, with the ability to present complex information clearly and persuasively to diverse audiences.
● Leadership Skills: Multidisciplinary project team leadership experience and a demonstrated ability to lead complex projects.
Preferred Qualifications:
● Familiarity with the use of patient-derived organoid (PDO) models for target identification and validation, biomarker discovery, and identifying a drug’s mechanism of action (MOA) or preclinical proof-of-concept (POC).
● Experience with early-stage drug development, including target discovery and biomarker identification.
● Experience analyzing single-cell RNA sequencing and spatial transcriptomics.
● Proficient in computational biology packages and environments including Pandas, NumPy, SciPy, Scikit-learn, Jupyter Notebooks, RStudio, tidyverse, ggplot, Git, Docker, and AWS.
● Experience with R package development.
● Comfort in a client-facing role with prior consulting and/or client-facing experience.
● Ability to thrive in a fast-paced environment and willingness to shift priorities seamlessly.
NYC/SF: $145,000-$190,000 USD
The expected salary range above is applicable if the role is performed from California and may vary for other locations (Colorado, Illinois, New York). Actual salary may vary based on qualifications and experience. Tempus offers a full range of benefits, which may include incentive compensation, restricted stock units, medical and other benefits depending on the position.
Additionally, for remote roles open to individuals in unincorporated Los Angeles – including remote roles- Tempus reasonably believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment: engaging positively with customers and other employees; accessing confidential information, including intellectual property, trade secrets, and protected health information; and appropriately handling such information in accordance with legal and ethical standards. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
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