Machine Learning Scientist - Bay Area, CA
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 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 Will Do:
- Analyze and integrate large diverse clinical, molecular 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.
- 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.
Required Qualifications:
- MS/PhD degree in a quantitative discipline (e.g. statistical genetics, cancer genetics, machine learning, bioinformatics, statistics, computational biology, applied mathematics, physics, or similar).
- Outstanding analytical and problem solving skills, with a particular focus on understanding the intricacies of molecular or multi-modal data sets.
- Experience working with genomic, clinical, or imaging data.
- 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.
Preferred Qualifications:
- Strong peer-reviewed publication record.
- 2+ years full time employment or postdoctoral experience building and validating predictive models on structured or unstructured data.
- Experience with: Git, matplotlib, seaborn, HTML5, CSS3, JavaScript, D3, Plot.ly, Flask, Dask, Docker, AWS.
- Experience working in a Linux / Mac and AWS cloud environments.
- Experience in agile environments and comfort with quick iterations.