Data Analyst

Vladimir Kogan

Email: *************@*****.***

Phone: 805-***-****

EDUCATION

Ph.D. Biostatistics.

University of Southern California (USC), Los Angeles, CA (12/2018) GPA: 3.926/4.0 Honors: Recipient of Rose Hills PhD Fellowship. Relevant Coursework:

Statistical Theory, ANOVA/Regression, Multivariate Analysis, Experimental Design, Generalized Linear Models, Epidemiology, Spatial Statistics, Clinical Trials

M.S. Mathematics-Statistics.

California State University (CSULB), Long Beach, CA (05/2012)

Relevant Coursework:

Statistical Inference, Computational Statistics, Nonparametric Statistics, Mixed Models, Data Mining methods (K-means clusters, decision trees, neural networks using SAS Enterprise Miner)

B.S. Applied Mathematics.

University of California, Los Angeles (UCLA), Los Angeles, CA (03/2010)

Relevant Coursework:

Probability Theory, Linear Models, Multivariable Calculus

SKILLS

-Clear understanding of statistical terms and concepts.

-Able to communicate results and findings to non-statisticians.

-Ability to plan tasks and meet deadlines.

-Capacity to work alone and within teams with limited supervision.

-High level of accuracy and attention to detail in all work.

Subject matter skills

-Broad experience with methods used in genomic data analysis, including genome- wide association studies (GWAS).

•More than 4 years of analyzing genomic data for observational studies.

•More than 3 years of writing simulations in R.

•Developed a statistical method for analyzing interaction between sets of variables intended for applications to genomic data.

-Familiar with statistical methods used in prospective cohort studies, clinical research, and survey work.

•Have taken coursework and served as a teaching assistant for Experimental Design class.

•Have taken coursework in survey sampling and related topics.

Statistical programming/computing and software skills:

-Proficient in R with more than 6 years of practical experience with advanced modeling, simulation, and figures and plots. Developed R-package CASI.

-Proficient in SAS with more than 6 years of practical experience with advanced modeling, data manipulation, and macros.

-Proficient in STATA with more than 2 years of experience.

-Proficient in SPSS with 1 year of experience.

-More than 6 years of experience with large data management using SAS and R.

-Extensive experience using PLINK throughout genomic research.

-Experience with software intended for genomic data analysis and observational studies, including UCSC Genome Browser, Broad Institute, HaploView, snp.plotter (R package), and Eigensoft.

-Experience with BASH Script and High-Performance Computing (HPC).

-Experience with EPICURE data analysis software, including DATAB, AMFIT, and GMBO.

-Have taken a course in Python developed by Google through coursera.org, called “Crash Course in Python”.

-Practical experience with Python, including writing and modification of code during application of new statistical method to the study of the effects of radiation dose on breast cancer, and through formal seminars on the basics of the programming language.

PROFESSIONAL EXPERIENCE

Employment

01/2019-present

Research data analyst - full-time

University of California, San Francisco (UCSF). San Francisco, CA

Implemented generalized linear models, including logistic, Poisson, and Cox proportional hazard model among others. Models focused on the excess relative risk for describing exposure-response and effect modification.

oCreated stratified person-year tables, including stratification on multiple time scales and time-dependent factors such as lagged cumulative doses.

oApplied models and methods for a wide variety of medical, public health, and epidemiological data.

Studied effects of radiation on risks to health such as breast cancer, lung cancer, diffuse goiter, and cardiovascular disease.

oCanadian Fluoroscopy Cohort Study.

oCohort of children and adolescents who lived in territories contaminated by the Chornobyl fallout in Ukraine and Belarus.

oBelarusian-American Cohort Study of Thyroid Cancer and Other Thyroid Diseases.

oEldorado Cohort Analysis of Incident Lung Cancer by Histological Subtype.

Worked with novel statistical method to estimate risk using data from a dosimetry system that characterized uncertainties in organ radiation doses.

08/2012-12/2018

Research Assistant – 20 hrs a week

University of Southern California (USC). Los Angeles, CA

Worked with genomic, environmental, epidemiologic, and health data.

Applied parametric and nonparametric statistical methodology to SNP, haplotype, methylation, and gene expression association studies.

Analyzed data on exposure to environmental hazards and diet from large scale prospective cohorts.

Data sets with which I worked include ABRIDGE (Asthma Bio-Repository for Integrative Genomic Exploration), CHS (Children’s Health Study), and CHARGE (Childhood Autism Risks from Genetics and the Environment).

Major theme of my methodological work was the study of various approaches to detecting statistical interaction with applications to genetic and epigenetic components of the genome, genetics and environmental exposures, and diet and environmental exposures.

Data analysis of genomic data entailed LD & haplotype block analysis, haplotype population frequency estimation, phasing of genotype data, filtering of SNP data for quality, and visualization and plotting of genome association results.

Phenotypes of interest in the applied part of my work included asthma and autism. All work required collaboration with faculty in Biostatistics, Environmental Health, and Mental Health departments as well as medical doctors.

Statistical programming component of my research included interaction with and submitting of code written in R to the High-Performance Computing Cluster (HPCC) using Unix script. In addition to R I utilized SAS, STATA, PLINK, UCSC Genome Browser, Broad Institute, HaploView, snp.plotter (R package), Bioconductor, and Eigensoft, among other software to complete tasks and contribute to research articles.

Used R, SAS, and STATA extensively to generate figures and text for grant applications and publications.

My work resulted in publication of two papers and successful grant application.

08/2012-12/2018

Teaching Assistant – 20 hrs a week

University of Southern California (USC). Los Angeles, CA

Assisted in teaching courses in Biostatistics, Data Analysis, Experimental Design, and Epidemiology.

Taught students statistical and data analysis concepts.

Assisted students with SAS, R, STATA, SPSS, and PASS (statistical power analysis) statistical software.

TA duties included grading, teaching, and responding to student questions in a timely manner.

07/2009-08/2011

Statistician – full-time

Amonix - Designer and manufacturer of commercial photovoltaic (CPV) solar power systems. Seal Beach, CA

Conducted modeling of electricity generation capacity of solar towers under various environmental conditions.

PUBLICATIONS

Kogan V, Millstein J, London SJ, Ober C, White SR, Naureckas ET, Gauderman WJ, DJ Jackson, Barraza-Villarreal A, Romieu I, Raby BA, Breton CV. Genetic-Epigenetic Interactions in Asthma Revealed by a Genome-Wide Gene-Centric Search. Hum Hered. 2019 Jan 22;83(3):130-152. doi: 10.1159/000489765. [Epub ahead of print]

Schmidt RJ, Kogan V, Shelton JF, Delwiche L, Hansen RL, Ozonoff S, Ma CC, McCanlies EC, Bennett DH, Hertz-Picciotto I, Tancredi DJ, Volk HE. Combined Prenatal Pesticide Exposure and Folic Acid Intake in Relation to Autism Spectrum Disorder. Environ Health Perspect. 2017 Sep 8;125(9):097007. doi: 10.1289/EHP604.

ABSTRACT PRESENTATIONS

Genetic-Epigenetic Interactions in Asthma Revealed by a Genome-Wide Gene-Centric Search

International Conference on Intelligent Biology and Medicine (ICIBM 2018)

June 10-12, 2018, Los Angeles, CA, USA

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