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Dr. Mithilesh Dronavalli

Medical Biostatistician/Data Scientist

Statistical Consulting
Biostatistics
Machine Learning
Statistical Programming
Social & Public Health Research
Employed Available
An Accredited Statistician (AStat), Data Scientist and medical doctor with nine years of experience in applying advanced statistical modelling and machine learning to clinical, public health and social research. Expertise in managing and analysing large-scale population datasets (1.8 million+ records) using R and Stata.

Proven track record of leading research projects from conception to publication with a focus on statistics and data science. Statistical author on 28 articles in peer-reviewed journals with over 750 citations.

My research is in the areas of poverty, crime, social disadvantage, prenatal drug abuse, prematurity, children with disabilities, mental health, out of home care, addiction, Aboriginal Health, communicable diseases, cancer, heart disease, smoking cessation, breastfeeding, health and well-being, health education and aged care.
Statistical / Database Programming R, Stata, Python, PL/SQL, SAS Reproducible well commented segmented code

Statistical Consulting Clear written and verbal communication, interested, organised, excellent problem solving,

Study Design Critical Appraisal, Systematic Reviews, Meta-Analysis, Meta-regression

Statistical Techniques: Generalised Linear Models, Longitudinal/Correlated Outcome Data/Multilevel Modelling, Survival Analysis, Multiple Imputation, generating and simulating
data

Causal Inference Directed Acyclic Graphs, Propensity Scores, Inverse Probability Treatment
Weights, Regression Discontinuity, Differences in Differences, Instrumental Variables, Mendelian Randomisation, Causal Mediation Analysis (incl. sensitivity analysis, time to event,
multiple mediators)

Machine learning Random Forest, Longitudinal K-means, SVM, KNN, Classification and Regression Trees, Linear and generalised models for prediction,

Visualisations Qlik, RStudio (for interactive live visualisations)

Teaching and Supervision of Research Students

Data Management of large linked population data

RCTs Clinical Trials Design, Sample Size, Randomisation Schedule,

Simulation Modelling AnyLogic: Agent Based Simulation, Discrete Events and System Dynamics

Accredited Statistician since 2022: (Statistical Society of Australia)
Member Profile: https://www.statsoc.org.au/Sys/PublicProfile/48202292/4702721
Criteria: Degree in Statistics +
6 years of progressively advanced Statistical Experience + Submission of Major Works +
Maintaining Continual Professional Development + 5 year re-accreditations