Tempus
Scientist II, Real World Data Science - Translational Research
Tempus, Redwood City, California, United States, 94061
With the advent of genomic sequencing, we can finally decode and process our genetic makeup; however, computer technology has had limited impact in healthcare. With the expansion of multi-modal healthcare data and recent advancements in AI, that’s about to fundamentally change. Tempus is a healthcare technology company at the forefront of that change to leverage data to improve patient lives.
Tempus' proprietary platform connects an entire ecosystem of real-world data to deliver real-time, actionable insights to physicians. Our data empowers researchers to better characterize and understand disease, and to drive better outcomes through precise, individualized care.
The
Scientist II, Life Sciences Research
will execute research projects for early stage biopharmaceutical partners. This role involves performing complex computational analyses and providing interpreted insights to guide decision-making for biopharma clients. The ideal candidate will possess strong genomic analytical skills and the ability to communicate complex scientific findings to various stakeholders. Key Responsibilities: Independent Contribution:
Independently execute complex translational research projects integrating molecular and clinical data from Tempus multimodal data platform to derive real-world insights for biopharma partners. Scientific Communication:
Present scientific findings clearly and meaningfully to diverse sets of external stakeholders. 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 team. Qualifications: Education:
PhD degree in a quantitative discipline (e.g., Biostatistics/Statistical Genetics, Cancer Genetics, Bioinformatics, Computational Biology, Computational Immunology or similar) or a PhD in Molecular Biology or Immunology combined with a very strong record of computational biology. Alternatively, an MSc degree with 4+ years of industry experience. Technical/Scientific Skills:
Highly proficient in R (ideally Rmd and/or RShiny). 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.
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Scientist II, Life Sciences Research
will execute research projects for early stage biopharmaceutical partners. This role involves performing complex computational analyses and providing interpreted insights to guide decision-making for biopharma clients. The ideal candidate will possess strong genomic analytical skills and the ability to communicate complex scientific findings to various stakeholders. Key Responsibilities: Independent Contribution:
Independently execute complex translational research projects integrating molecular and clinical data from Tempus multimodal data platform to derive real-world insights for biopharma partners. Scientific Communication:
Present scientific findings clearly and meaningfully to diverse sets of external stakeholders. 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 team. Qualifications: Education:
PhD degree in a quantitative discipline (e.g., Biostatistics/Statistical Genetics, Cancer Genetics, Bioinformatics, Computational Biology, Computational Immunology or similar) or a PhD in Molecular Biology or Immunology combined with a very strong record of computational biology. Alternatively, an MSc degree with 4+ years of industry experience. Technical/Scientific Skills:
Highly proficient in R (ideally Rmd and/or RShiny). 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.
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