Data Scientist

Job Description

Job Function Summary: Involves developing and utilizing computational tools and systems to analyze and interpret biological or other research data. Utilizes and develops algorithms, computational techniques, and standard statistical methodologies. Helps in the design of new experiments and leads the execution of building machine learning and statistical models. Implements end-user needs in database development, maintenance, searching, and integration. Maintains computational infrastructure and manages and tracks the flow of samples and information for large-scale studies. Provides bioinformatics and access to public and proprietary databases. Manages cloud and on-premises computational infrastructure and data.

About the Role

Our research efforts are at the intersection of cardiovascular disease and human genetics. Our clinical research efforts employ new techniques for deep phenotyping, such as deep learning. But these techniques rely on a solid foundation of classical bioinformatics. The Bioinformatics Programmer/Data Scientist will assist in managing, cleaning, and analyzing large scale medical data using a wide variety of analytic techniques, both in the cloud and with on-premises compute depending on data permissions.

Responsibilities

• Designs, develops, debugs and utilizes computer programs necessary to extract, transform, and load data and prepare it for analysis.
• Assists in extracting, transforming, and loading data from clinical sources and research sources using a wide variety of analytic techniques.
• Develops data pipelines to standardize and automate repeatable data processing steps as appropriate.
• Builds and runs programs to extract relevant imaging, biosignals, and medical data from clinical systems, including UCSF data. Performs data quality control.
• Utilizes standard software tools to analyze, interpret or create moderately complex biological or research data.
• Uses software such as plink2 to manage, merge, split, and analyze sequencing and genetic imputation data.
• Performs quality control at the sample-, variant-, and genotype-level for genetic sequencing and imputation data.
• Conducts analyses with linear, logistic, or survival models where appropriate.
• Assists with computational resource management.
• Assists with management of research databases and shared computational resources.
• Manages cloud virtual environments.
• Manages containerization with tools such as Docker.
• Aids in report preparation and / or analysis for internal constituents and scientific publication and dissemination.
• Describes methods, results and implications of the work.
• Conducts background bibliographic research and summaries of the latter if appropriate for documents to be published externally.
• Generates appropriate data visualizations.
• Aids in general manuscript preparation and submission.
• Maintains code and documentation, communicates proactively.
• Writes internal-facing documentation for all analyses, coding, tooling, and pipelines, clearly describing in text and graphics what is done and why it is done this way.
• Writes appropriate code comments explaining unintuitive decisions, algorithms, and functions to allow other lab members to reason clearly about the code.
• Uses change-management software, including git for code management.
• Proactively communicates to the PI about barriers to progress and possible code or workflow improvements.
• Provides the PI and collaborators with recommendations and guidance for subsequent steps.

Qualifications

• Bachelor's degree in biological science, computational / programming, or related area and / or equivalent experience / training.
• 12 months or more of demonstrated work experience using medical and/or health-related data, or similar, including developing pipelines for extracting, transforming, and loading data, and data analysis.
• Working knowledge of bioinformatics methods and data structures.
• Working knowledge of biostatistics and basic statistical testing.
• Working knowledge of systems programming and databases.
• Working knowledge of application and data security concepts.
• Ability to effectively manage time and see assigned parts of projects through to completion on deadline.
• Basic consultation and communication skills.
• Demonstrated fluency and competency with statistical programming with the R programming language or the Python programming language.
• Experience with or a demonstrated ability to learn and implement data management and computational pipelines for management of large-scale data.
• At least 6 months of experience in direct data management and analysis using medical and/or health-related data using the above tools.
• Ability to lead and maintain data pipelines for real-time data acquisition from clinical systems.
• Ability to multi-task and work well with limited supervision.
• Working project management skills.
• Interpersonal skills in order to work with both technical and non-technical personnel at various levels in the organization.
• Ability to communicate technical information in a clear and concise manner.
• Self-motivated, able to learn quickly, meet deadlines and demonstrate problem-solving skills.