Research Data Analyst I

Generic Scope Entry-level professional with limited prior experience; learns to use professional concepts to resolve problems of limited scope and complexity; works on assignments that are initially routine in nature, requiring limited judgment and decision making. Employees at this level are expected to acquire the skills and knowledge to perform more advanced work following an agreed upon time in position, through defined training and development planning.

Custom Scope Under direct supervision, acquires skills and knowledge of professional concepts in research data management and analysis. Works on small projects or segments of projects with limited scope and complexity. Follows standard programming procedures to analyze situations and data from which answers can be readily obtained.

Department Overview The Quandt lab at the UCSF Diabetes Center is seeking to hire a highly motivated Research Data Analyst to join a team of clinical and research collaborators studying mechanisms of immune tolerance in patients with autoimmune diseases such as type 1 diabetes and endocrine side effects of cancer immunotherapy and mouse models of autoimmunity in collaboration with the Anderson Lab. The Research Data Analyst will aid in the lab’s data management, computational methods and provide essential bionformatics support in the analysis of various experimental data pipelines, including genetic risk scores, PhIP-Seq, single-cell RNA-seq, and ATAC-seq.

Responsibilities Gather and organize various types of research data. Analyze research datasets according to the pipelines established in the labs. Prepare figures and tables summarizing results in support of research proposals, protocols, and reports.

Contribute to scientific manuscripts, publications, and presentations. Maintain research data collection, retrieval, and reporting systems. RESPONSIBILITIES Research Data Collection and Preparation Collects research data and prepares it for analysis.

Research Instruments and Data Sources Supports testing of research instruments and data sources. Data Reporting Products Assists with evaluation and research of data reporting products. Single-Cell Data Analysis Assists in analysis of single cell RNA-seq and ATAC-seq data.

PhIP-Seq Data Analysis Assists in analysis of large data sets of Phip-Seq data. Data Science Research Assists with data science research to contribute to proposals for other researchers and Principal Investigators from the organization. Computer Programming Creates, maintains, documents and utilizes computer programs of limited algorithmic complexity and scale.

Predictive Analytics and AI Under direct supervision or collaboration with peers, utilizes basic algorithms, techniques, AI and statistical methodologies to conduct predictive analytics, or generate insights. Data Storage and Documentation Develops knowledge in areas of storage, documentation and dissemination of computerized data. Required Qualifications Acquiring knowledge of research function.

Acquiring ability to perform research analysis duties. Acquiring statistical analysis, systems programming, and database design skills to perform research analysis duties. Ability to effectively manage time and see assigned parts of projects through to completion on deadline.

Familiarity with basic data science workflows and statistical modeling applications is required. Proficiency in both Python and R programming languages. Direct hands-on experience in bioinformatics and computational biology research.

Interpersonal skills in order to work with both technical and non-technical personnel at various levels in the organization; and to iteratively improve data science methodologies working with biomedical domain experts. Ability to communicate technical information in a clear and concise manner. Additional Qualifications Basic consultation and communication skills.

Excellent verbal and written communication skills with the ability to integrate and communicated complex information. Excellent organizational skills. Ability to work independently and as a member of an interdisciplinary research team.

Ability to prioritize tasks, coordinate work with others, and meet multiple deadlines. Experience with R and Python programming. Familiarity with basic data science workflows.

Required Education Bachelor's degree in related area and / or equivalent experience / training. Coursework in biological sciences. Coursework in computer sciences.

Full time · Day shift