Genomic Data Scientist (Hereditary Disease)

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

Passionate about precision medicine and advancing the healthcare industry?

Recent advancements in genomics and computer 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 seeking a genomics data scientist with experience in supporting innovative research by managing and modelling large volumes of clinical, genetic and/or genomic data. You will work on data ingestion, organization, and implementation of analysis workflows for large-scale human cohorts with genetic and multi-dimensional, multi-modality phenotypic data. These will be obtained from public sources, as well as private datasets generated in-house and obtained through our collaborations. This position is based on the San Francisco Bay Area.

Responsibilities

• Bring in genomics/genetics datasets from external and internal sources to help develop internal resources for various analytical approaches
• Develop scalable and high quality analysis pipelines for clinical trials and clinical diagnostics products.
• Leverage the opportunities and efficiencies afforded by access to hybrid cloud-based, distributed ecosystem of database technologies
• Collaborate with other data scientists and statistical geneticists to leverage multimodal data in training polygenic risk scores, machine learning, and other predictive models.
• Work with scientists and clinicians to design and perform analyses on clinical sequencing data that generate clinically actionable insights in order to improve quality of care.
• Produce high quality and detailed documentation for all projects.

Required Experience

• PhD/Masters or equivalent experience in genetics, biomedical informatics, or related life sciences areas.
• At least years of experience in complex data analysis and familiarity with applications of FAIR principles
• Hands-on development of database systems and data manipulation using SQL, working within a POSIX CLI environment
• Computational skills using Python (strongly preferred), Java, C/C++ or other programming languages.
• Good understanding of life sciences domain and omics technologies.
• Experience with longitudinal human clinical/phenotype data, e.g. from electronic health records, epidemiological cohorts, or clinical trials.
• Experience with genetic and genomic data types, including public genetic databases and results data from high-throughput genetic assays (e.g. UK Biobank, Gnomad, etc.) is a plus.

Ideal Candidates Will Possess

• Experience with Python/Jupyter notebooks, NumPy/Pandas, and/or R/Bioconductor in analyzing large data sets.
• Experience mining modern, large-scale genetic databases (e.g. ExAC/gnomAD, UK Biobank, UK10K, EBI GWAS Catalog, 1KG, etc.).
• Experience with distributed database technologies and related big-data analysis tools (e.g. Spark, BigQuery; the Apache Hadoop/Hive ecosystem). 
• Ability to communicate insights and presenting concepts
• Self-driven and works well in interdisciplinary teams.
• Track record of publications in related domains is a plus.

Candidates based on the SF Area with current authorization to work in the US are strongly preferred.