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 looking for machine learning, deep learning, and data science experts who are passionate about applying state of the art techniques to the processing and integrative analyses of vast amounts of data. The ideal candidate has significant expertise in the biomedical or clinical domain, and is eager to apply his or her skills to improve patient outcomes
What You'll Do
- Analyze and integrate large diverse clinical, molecular, biosignal and imaging datasets to extract insights, and drive research opportunities.
- Design and prototype novel analysis tools and algorithms for predicting patient outcome and treatment response in oncology and cardiology
- Collaborate with product, science, engineering, and business development teams to build the most advanced data platform in precision medicine.
- Interrogate analytical results for robustness, validity, and out of sample stability.
- Document, summarize, and present your findings to a group of peers and stakeholders.
- Provide technical leadership & expertise across multiple modeling projects.
- MS/PhD degree in a quantitative discipline (e.g. statistical genetics, cancer genetics, machine learning, bioinformatics, statistics, computational biology, applied mathematics, physics, or similar).
- 5+ years full time employment or postdoctoral experience building and validating predictive models on structured or unstructured data
- Outstanding analytical and problem solving skills, with a particular focus on understanding the intricacies of molecular or multi-modal data sets.
- Strong experience working with genomic, biosignal, clinical, or imaging data.
- Expert-level experience with supervised and unsupervised machine learning algorithms, and ensemble methods, such as: PCA, regression, deep neural networks, decision trees, gradient boosting, generalized linear models, mixed effect models, non-linear low dimensional embeddings and clustering.
- Proficient in Python and SQL.
- Experience with the following: Pandas, NumPy, SciPy, Scikit-learn, Jupyter Notebooks, and a machine learning framework such as TensorFlow, SageMaker, or PyTorch
- Strong programming skills.
- Thrive in a fast-paced environment and willing to shift priorities seamlessly.
- Experience with communicating insights and presenting concepts to diverse audiences.
- Team player mindset and ability to work in an interdisciplinary team.
- Goal orientation, self motivation, and drive to make a positive impact in healthcare.
Nice to Haves
- Strong peer-reviewed publication record.
- Kaggle.com competitions and/or kernels track record
- Experience working in a Linux / Mac and AWS cloud environments.
- Experience in agile environments and comfort with quick iterations.
- Technical leadership experience.