Research Data Analyst (8273C), School of Public Health - #88230

Summary

The University of California, Berkeley, particularly its School of Public Health and Center for Targeted Machine Learning and Causal Inference, advances interdisciplinary research in public health, causal inference, and artificial intelligence. The Research Data Analyst conducts statistical analyses for a domestic HIV prevention research program, builds and documents analytic datasets, implements analyses in R, supports reporting and publications, and coordinates data requests across study sites.

Responsibilities

• Implement pre-specified analyses for randomized trials and related studies under the direction of the lead statistician, including descriptive summaries, primary and secondary outcome analyses, and pre-specified sensitivity analyses. Apply established causal inference and machine learning based estimators (for example TMLE and related R packages) using specifications set by the lead statistician. Independently plan and run limited analyses and simulations addressing defined design or power questions
• Build, document, and maintain pooled analytic datasets from the three site datasets and from Electronic Health Records (EHR) and administrative sources. Write and maintain reproducible derivation code. Specify what is needed from site data managers and verify that delivered data meet analytic requirements
• Contribute to the drafting of statistical analysis plans, including data source descriptions, analytic population and outcome definitions, table and figure shells, and written specification of analyses for review by the lead statistician. Maintain version-controlled code, data dictionaries, and analysis logs so all reported results can be regenerated. Contribute analytic language to protocols and Institutional Review Board (IRB) submissions
• Prepare recurring monitoring reports, DSMB tables, and grant progress reporting for internal study constituents. Produce and format tables and figures for manuscripts, abstracts, and slide presentations to journal, sponsor, and meeting specifications. Run reviewer-requested analyses as specified and assemble supplementary materials
• Work routinely with site data managers and study staff at the three sites on data deliveries, variable questions, and turnaround of analytic requests. Respond to enrollment, retention, and cohort description requests from co-investigators and study staff
• Participates in workshops, trainings, and other professional development activities; may participate in committees, projects, and other service activities
• Other duties

Skills

• Working knowledge of biostatistical principles and epidemiologic study designs, including randomized controlled trials, observational studies, cohort studies, and longitudinal analyses
• Working Knowledge of established causal inference and machine learning methods (e.g., TMLE, propensity scores, inverse probability weighting) and their application using R
• Working skills in conducting statistical analyses, including descriptive, primary, secondary, sensitivity, and simulation analyses according to predefined statistical analysis plans
• Proficiency in programming with R and developing reproducible, well-documented analytic workflows and statistical code
• Ability to coordinate effectively with multidisciplinary investigators, statisticians, research staff, and collaborating sites to support timely data requests and study deliverables
• Strong organizational, analytical, and problem-solving skills with the ability to manage multiple priorities while maintaining accuracy and attention to detail
• Ability to maintain confidentiality, comply with human subjects research regulations, and effectively communicate statistical findings to diverse scientific and non-technical audiences
• Demonstrated effective communication and interpersonal skills
• Demonstrated ability to communicate technical information to technical and non-technical personnel at various levels in the organization
• Self-motivated and works independently and as part of a team
• Able to learn effectively and meet deadlines
• Demonstrated complex problem-solving skills
• Bachelor's degree in related area and / or equivalent experience / training
• Advanced degree in related area (Preferred)

Qualifications

Must Haves

• Working knowledge of biostatistical principles and epidemiologic study designs, including randomized controlled trials, observational studies, cohort studies, and longitudinal analyses
• Working Knowledge of established causal inference and machine learning methods (e.g., TMLE, propensity scores, inverse probability weighting) and their application using R
• Working skills in conducting statistical analyses, including descriptive, primary, secondary, sensitivity, and simulation analyses according to predefined statistical analysis plans
• Proficiency in programming with R and developing reproducible, well-documented analytic workflows and statistical code
• Ability to coordinate effectively with multidisciplinary investigators, statisticians, research staff, and collaborating sites to support timely data requests and study deliverables
• Strong organizational, analytical, and problem-solving skills with the ability to manage multiple priorities while maintaining accuracy and attention to detail
• Ability to maintain confidentiality, comply with human subjects research regulations, and effectively communicate statistical findings to diverse scientific and non-technical audiences
• Demonstrated effective communication and interpersonal skills
• Demonstrated ability to communicate technical information to technical and non-technical personnel at various levels in the organization
• Self-motivated and works independently and as part of a team
• Able to learn effectively and meet deadlines
• Demonstrated complex problem-solving skills
• Bachelor's degree in related area and / or equivalent experience / training

Nice to Haves

• Advanced degree in related area (Preferred)

Benefits

• All full-time staff employees receive at least 80 hours of paid professional development time per year.
• This is a full-time (40 hours/week) Career position eligible for UC benefits.
• This position is eligible for up to 5 days/week of remote work within the United States. Exact arrangements are determined in partnership with your supervisor to meet role responsibilities and department needs and are subject to change.