Sima Sharghi

About Sima Sharghi

Turning clinical data into rigorous evidence | PhD Statistician | Clinical Study Design | Bayesian & Longitudinal ModelingWelcome to my world of statistics and clinical research. With over 15 years of formal training and applied experience, I specialize in designing statistically rigorous studies and translating complex clinical questions into meaningful, decision-ready evidence. PhD in Statistics : Advanced training in Bayesian and frequentist methods, causal inference, longitudinal modeling, and simulation-based study design. Clinical Research & Study Design Leadership : Extensive experience collaborating with physician investigators to develop clinical research protocols, define endpoints, perform sample size justification, and design longitudinal and observational studies. Postdoctoral Research & NIH-Funded Collaborations : Methodological leadership on large-scale health research programs, applying causal inference and advanced statistical methods to real-world clinical and public health data. Real-World Healthcare Data Expertise : Deep experience working with electronic health record data (Epic Clarity, Caboodle, Cosmos), supporting clinical research, disease modeling, and evidence generation. Bayesian Modeling & Simulation : Developed Bayesian models and conducted simulation studies to evaluate study design performance, supporting robust and reliable statistical inference.I am passionate about advancing clinical research through rigorous statistical thinking and collaborative scientific discovery. I welcome opportunities to contribute to clinical development, translational research, and evidence generation efforts that improve patient outcomes.

Experience

1. Senior Statistician

   Akron Children's

   Sep 2024 — Present

   Lead statistical study design and protocol development for prospective and observational clinical research studies, including endpoint definition, analytic strategy, sample size justification, and simulation-based design.• Develop Bayesian models and conduct simulation studies to evaluate operating characteristics of study designs, including statistical power and estimator performance.• Design and conduct longitudinal and causal analyses using electronic health record data to investigate disease progression, treatment effects, and clinical outcomes.• Apply causal inference and predictive modeling methods to real-world clinical data to support clinical research and risk stratification.• Collaborate closely with physician investigators to translate clinical questions into rigorous statistical frameworks, clinically meaningful endpoints, and publication-ready analyses.• Provide statistical leadership across multidisciplinary clinical research initiatives and communicate findings to clinical and scientific stakeholders.

Education

• Bowling Green State University

  Doctor of Philosophy (PhD), Statistics

• Bowling Green State University

  Master of Science (M.Sc.), Applied Statistics

  2014 — 2016