Tempus AI Inc.
Senior Computational Biology - Real World Data Science
Tempus AI Inc., Durham, North Carolina, United States, 27703
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.
The
Senior Scientist, Translational Research or Real-World Evidence
in the Real World Data Science org will design and execute research projects for early-stage to mid-stage biopharmaceutical partners. This role involves performing complex computational analyses and providing interpreted insights in a consultative approach to guide decision-making for biopharma clients. This role will require complex bioinformatics analyses to support a wide variety of projects. We are seeking a candidate with extensive experience in the analysis of high-dimensional data, cancer genomics, statistics, and machine learning.
Key Responsibilities:
Perform bioinformatics analyses for large-scale research projects, such as detailed target characterization, biomarker discovery, or identifying the ideal patient population for a specified therapeutic.
Project management, including creating research plans, executing research aims, supervising other bioinformaticians, and creating reports and other deliverables.
Develop methods for analyzing multi-omics data, building analysis pipelines, algorithms, and validating tools for oncology research.
Collaborate with scientists to understand their research questions and propose solutions.
Write clean, maintainable, documented code.
Independent Contribution:
Independently execute complex research projects integrating molecular and clinical data to derive real-world insights for biopharma partners.
Scientific Communication:
Expert in navigating client interactions; present scientific findings clearly and meaningfully to diverse sets of external stakeholders.
Document, summarize, and communicate highly technical results and methods clearly to non-technical audiences.
Continuous Improvement:
Stay current with industry trends, best practices, and advancements in computational oncology research. Apply this knowledge to enhance research methodologies and improve overall research quality on the team.
Qualifications:
Education:
PhD degree in a quantitative discipline (e.g. Biostatistics/Statistical Genetics, Cancer Genetics, Bioinformatics, Computational Biology, Computational Immunology, or similar) plus 2 years of experience or postdoctoral studies. Alternatively, a PhD in Molecular Biology or Immunology combined with a very strong record of computational biology.
Experience:
Minimum 2+ years in drug development leveraging genomic and multimodal data for drug discovery and development.
Technical/Scientific Skills:
Proficient in R, Python, and SQL. Strong understanding of cancer biology.
Communication Skills:
Excellent written and verbal communication skills, with the ability to present complex information clearly and persuasively to diverse audiences.
Preferred Skillsets/Background:
Strong understanding of molecular data and artificial intelligence in drug discovery with experience in integrative modeling of multi-modal clinical and omics data.
Previous experience working with large transcriptome and NGS data sets.
Prior consulting and/or client-facing experience is highly desirable.
Ability to work collaboratively in a team environment.
Thrive in a fast-paced environment and willing to shift priorities seamlessly.
Experience with R package development.
Strong peer-reviewed publication record.
Experience with: Pandas, NumPy, SciPy, Scikit-learn, Jupyter Notebooks, RStudio, R Package development, tidyverse, ggplot, Git, matplotlib, seaborn, HTML5, CSS3, JavaScript, D3, Plot.ly, Flask, Dask, Docker, AWS.
Goal orientation, self-motivation, and drive to make a positive impact in healthcare.
#J-18808-Ljbffr
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.
The
Senior Scientist, Translational Research or Real-World Evidence
in the Real World Data Science org will design and execute research projects for early-stage to mid-stage biopharmaceutical partners. This role involves performing complex computational analyses and providing interpreted insights in a consultative approach to guide decision-making for biopharma clients. This role will require complex bioinformatics analyses to support a wide variety of projects. We are seeking a candidate with extensive experience in the analysis of high-dimensional data, cancer genomics, statistics, and machine learning.
Key Responsibilities:
Perform bioinformatics analyses for large-scale research projects, such as detailed target characterization, biomarker discovery, or identifying the ideal patient population for a specified therapeutic.
Project management, including creating research plans, executing research aims, supervising other bioinformaticians, and creating reports and other deliverables.
Develop methods for analyzing multi-omics data, building analysis pipelines, algorithms, and validating tools for oncology research.
Collaborate with scientists to understand their research questions and propose solutions.
Write clean, maintainable, documented code.
Independent Contribution:
Independently execute complex research projects integrating molecular and clinical data to derive real-world insights for biopharma partners.
Scientific Communication:
Expert in navigating client interactions; present scientific findings clearly and meaningfully to diverse sets of external stakeholders.
Document, summarize, and communicate highly technical results and methods clearly to non-technical audiences.
Continuous Improvement:
Stay current with industry trends, best practices, and advancements in computational oncology research. Apply this knowledge to enhance research methodologies and improve overall research quality on the team.
Qualifications:
Education:
PhD degree in a quantitative discipline (e.g. Biostatistics/Statistical Genetics, Cancer Genetics, Bioinformatics, Computational Biology, Computational Immunology, or similar) plus 2 years of experience or postdoctoral studies. Alternatively, a PhD in Molecular Biology or Immunology combined with a very strong record of computational biology.
Experience:
Minimum 2+ years in drug development leveraging genomic and multimodal data for drug discovery and development.
Technical/Scientific Skills:
Proficient in R, Python, and SQL. Strong understanding of cancer biology.
Communication Skills:
Excellent written and verbal communication skills, with the ability to present complex information clearly and persuasively to diverse audiences.
Preferred Skillsets/Background:
Strong understanding of molecular data and artificial intelligence in drug discovery with experience in integrative modeling of multi-modal clinical and omics data.
Previous experience working with large transcriptome and NGS data sets.
Prior consulting and/or client-facing experience is highly desirable.
Ability to work collaboratively in a team environment.
Thrive in a fast-paced environment and willing to shift priorities seamlessly.
Experience with R package development.
Strong peer-reviewed publication record.
Experience with: Pandas, NumPy, SciPy, Scikit-learn, Jupyter Notebooks, RStudio, R Package development, tidyverse, ggplot, Git, matplotlib, seaborn, HTML5, CSS3, JavaScript, D3, Plot.ly, Flask, Dask, Docker, AWS.
Goal orientation, self-motivation, and drive to make a positive impact in healthcare.
#J-18808-Ljbffr