Niclette Kibibi

PhD-trained epidemiologist and data scientist with 7+ years of research and analytics experience turning complex real-world datasets into decision-ready insights. Advanced user of R and SAS with experience using SQL in analytical workflows and working knowledge of Python. Skilled in statistical modeling, Bayesian meta-regression, longitudinal and survival analysis, causal inference, data visualization, quality control, and reproducible pipelines.

Proven ability to independently lead analyses, communicate technical findings to multidisciplinary audiences, and mentor analysts.

Research Scientist at Institute for Health Metrics and Evaluation (IHME), University of Washington (2023-11 – 2025-09)

Led end-to-end analyses of large, heterogeneous global health datasets, translating complex epidemiologic data into estimates and insights used in scientific and policy-facing work.

• Developed reproducible R- and SQL-supported workflows for data cleaning, harmonization, validation, modeling, and quality assurance across multiple disease areas.
• Applied advanced statistical methods including regression modeling, Bayesian meta-regression, bias adjustment, longitudinal analysis, and evidence synthesis.
• Investigated data and model anomalies, evaluated source strengths and limitations, and implemented rigorous validation checks to improve analytical reliability.
• Created clear visualizations, technical documentation, reports, and presentations that communicated complex methods and findings to scientific and cross-functional stakeholders.
• Independently managed multiple analytical priorities while collaborating with epidemiologists, statisticians, clinicians, and data scientists.
• Mentored junior researchers and analysts and provided technical guidance on analytical methods, coding, and interpretation.

Graduate Research Assistant & NIOSH Fellow at University of Iowa (2018-08 – 2023-05)

Designed and executed observational studies using healthcare claims, electronic health records, registries, surveys, and population-level datasets.

• Built analytical workflows in R and SAS and applied propensity-score methods, generalized regression models, Kaplan-Meier methods, Cox regression, mixed-effects models, and longitudinal analyses.
• Analyzed complex real-world data to identify patterns, compare populations, assess healthcare utilization and outcomes, and communicate actionable findings.
• Led projects from research question and protocol development through data preparation, statistical analysis, visualization, interpretation, manuscript development, and presentation.
• Conducted systematic reviews and meta-analyses and contributed to peer-reviewed publications and scientific presentations.

Graduate Teaching Assistant at University of Iowa (2021-01 – 2022-12)

Taught intermediate data analysis and statistical programming using SAS and R; led journal clubs and mentored junior analysts in reproducible analytical practice.

PhD in Epidemiology – University of Iowa (2023)

Graduate Certificate in Biostatistics – University of Iowa (2022)

MPH in Health Policy & Ethics – Creighton University (2015)

BA in Biochemistry & Psychology – Eastern Mennonite University (2010)