Data Analysis Supervisor Oakland, CA,

Position: Data Analysis Supervisor 2  Oakland, CA, Job ID 83801
Data Analysis Supervisor 2 Oakland, CA, Job

University of California Agriculture and Natural Resources

Job Description

Position Summary:
Under the supervision of NPI's Director, the Data Analysis Supervisor 2 will function as an advisor to the unit on study design and analytical methods for research and evaluation studies focused on a range of nutrition and physical activity policies and programs and will supervise NPI's Data Analyst Section. Responsibilities include designing research methods and analysis plans; collecting, managing, and analyzing quantitative data;

disseminating findings to internal and external stakeholders; and managing and overseeing project timelines and deliverables. This position will manage the workload, professional development, and performance management of 3-7 research data analysts and staff research associates, as well as survey workers and students as needed.

Department Summary:
The Nutrition Policy Institute (NPI) is a statewide institute within the Division of Agriculture and Natural Resources at the University of California. NPI conducts and translates policy-relevant research to transform environments for healthy children, families, and communities. We are home to approximately 30-40 academic, staff and student employees located in the UCOP offices in Oakland and other locations.

This position is a career appointment that is 100% fixed.

The home department is the Nutrition Policy Institute (NPI). While this position normally is based in Oakland, CA, this position is eligible for hybrid flexible work arrangements for applicants living in the State of California at this time. Please note that hybrid flexible work arrangements are subject to change by the University.

Pay Scale: $/year to $/year

Job Posting Close Date:
This job is open until filled. The first application review date will be 2/23/2026.

Key Responsibilities:

40%

Supervision, consultation, and project management:
Provides direct supervision to data analyst section, as well as temporary staff such as survey workers and students, as needed. Performs supervisory functions including recruitment, performance reviews, training and handling disciplinary issues according to organization HR policies. Serves as a consultant to unit staff on appropriate research design and analytical methods. Develops workplans and timelines; organizes and chairs meetings/consultations with team members.

Responsible for statistical integrity, adequacy and accuracy of data, and the timeliness and effectiveness of all data collection and reporting systems.

10%

Study design and proposal development:
In consultation with NPI Director and research teams, designs research and evaluation studies and their data collection and analysis plans, including sampling, survey instruments, data entry programs, and results reports. Contributes to grant proposals for state, federal, and foundation funding.

25%

Statistical analyses:
Performs statistical analysis for individual research projects. Selects appropriate test formulas and performs computations such as multiple and partial correlation coefficients, t-tests, Chi-square, ANCOVA, linear and logistic regression, multilevel modeling, spatial analyses, interrupted time series models, latent class analysis, principal components analysis, structural equation modeling, multiple imputation, non-parametric analyses such as Mann-Whitney U tests and Wilcoxon signed rank tests, and power analyses for a variety of study designs.

Analyzes research data using statistical and geospatial software such as SAS, R, Stata, and ArcGIS. Prepares and summarizes preliminary and final data.

10%

Data management:
Creates, manages, and maintains project databases and organizational data systems. Checks data quality, cleans and records data, geocodes data, and creates derived datasets. Creates standard analytic data files and documents program codes and procedures for use by research team. Develops systems for organizing data to analyze. Applies advanced data management techniques such as macros and SQL programming to efficiently conduct data management and cleaning.

Some data collection and entry may be required.

15%

Dissemination:
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