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 complexresearch 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.
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