Sr Scientist II, Computational Discovery Science

Tempus; United States; On-site; USD 145,000 - 190,000; Full time

Job summary

Tempus, a leader in precision medicine, seeks a Senior Scientist II to join the Computational Discovery Science team. You will develop and apply computational methods to identify novel cancer targets, leveraging large clinico-genomic data and patient-derived organoid experiments, while collaborating with AI/ML scientists and lab biologists.

This highly collaborative role requires independent translational research leadership and the ability to communicate complex results to pharma and biotech

Qualifications

• PhD with strong publication record in genomics or multimodal data.
• 4+ years applying genomic and multimodal data with ML to cancer.
• Proficient in R, Python, SQL; deep cancer genomics/immunology knowledge.

Responsibilities

• Identify targets in patient sub-populations using multi-modal data.
• Apply in silico methods to Tempus Real-World Data to find patterns.
• Create embeddings to cluster patients and identify novel subtypes.
• Leverage Tempus Loop Agent architecture to prioritize analyses.
• Collaborate with modeling lab using CRISPR and PDO data for targets.

Skills

Python

R

SQL

Machine Learning

Genomics

Communications

Education

PhD in a quantitative discipline

Tools

Pandas

NumPy

SciPy

Scikit-learn

Jupyter Notebooks

RStudio

tidyverse

ggplot

Git

Docker

AWS

Job description

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

• 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 compensati