Nishan Mudalige, PhD

adzcts@r.postjobfree.com https://nishanmudalige.github.io https://github.com/nishanmudalige Vancouver, BC WORK EXPERIENCE

Senior Statistician Mar 2023 – Aug 2023

Centre for Advancing Health Outcomes Vancouver, BC

Conducted statistical research on projects to support the health economics research unit using SAS, R and SQL.

Presented numerical and visual statistical summaries related to surveillance data of various populations in BC.

Utilized SQL in SAS to filter and merge data to create an updated cohort data sets for analysis.

Presented and explained results of analysis to project partners and team members. Senior Statistician Jul 2021 – Mar 2023

Provincial Health Services Authority Vancouver, BC

Conducted statistical analysis on projects supporting initiatives aimed at providing residents in BC with the best possible healthcare using SAS, R, Excel and SQL and through the cloud (Microsoft Azure platform).

Applied statistical knowledge to evaluate a health technology assessment (classified); conducted analysis on various projects related to COVID-19 infections, vaccinations and rapid antigen tests.

Utilized SAS and SQL to develop an analytic data set for a health technology assessment with advice from doctors.

Analyzed sub-populations within BC, such as critically extremely vulnerable (CEV), Indigenous, 60+ and minors.

Assisted external hematologists analyze vaccinations of CEV populations.

Utilized Power BI and Tableau to analyze data flows. Postdoctoral Fellow in Statistics Oct 2020 – Jul 2021 Université Laval Québec City, QC (worked remotely from Victoria, BC)

Developed machine learning algorithms and optimizers in R to model branching structures of trees in nature.

Project conducted in collaboration with a research group at McGill University with code maintained on GitHub.

Contributed to a peer reviewed publication (Learning how a tree branches out: A statistical modeling approach) and an R package (TreeBranchModeller) which resulted from this research.

Supported by Canadian Statistical Sciences Institute fellowship (Selective). Beran Estimation of the Fisher–Bingham and Kent Distributions (PhD Thesis) Sep 2016 – Oct 2020 University of Guelph Guelph, ON

Solved a problem related to statistical models over a high-dimensional structure that had been unresolved for 40 years by establishing the theory for a new class of model which captures the structure of data over surface.

Developed code in R and Python based on the new models created and implemented variations of modern machine learning techniques to run simulations on high performance computers using SSH and cloud computing.

Research resulted in the following R packages: spherical.LASSO, general.spherical, s.harmonic, watson.kernel. Software Programming Consultant Jan 2020 – May 2020 Centre for Biodiversity Genomics Guelph, ON

Trained and assisted a co-op student develop an R package called BOLDvalidatoR which assists researchers determine the validity of taxonomic data prior to uploading it to the Barcode of Life Database System (BOLD).

Presented at meetings with data managers and the informatics team to discuss progress and development.

Tested BOLDvalidatoR and created a help manual for BOLDvalidatoR which includes vignettes and examples. Software Programming Assistant Jul 2017 – Aug 2018 Centre for Biodiversity Genomics Guelph, ON

Developed, tested, documented and implemented a fully functioning R package called BOLD.R to interface with the Barcode of Life Database (BOLD) system directly through R. This package allows users to access their private data or public data directly into R for statistical analysis (http://boldsystems.org/bold.r).

Worked closely with an interdisciplinary team of biologists, ecologists, computer scientists and data managers.

BOLD.R was developed and maintained using git on GitHub.

BOLD.R has been presented at 4 conferences (3 posters) in 3 countries and published in conference proceedings.

Assisted lead programmer test an optimizer for a microarray device with Python to improve the sequencing pipeline.

Investigated data-mining project techniques related to predicting abundance.

Developed code to estimate resources consumed by Gearman job server processes in DNA barcoding. RELATED WORK EXPERIENCE

Teaching Assistant in Data Analytics Jan 2020 – Aug 2020 University of Guelph

Selected for this competitive position in data analytics sponsored by KPMG professional consultants.

Supported professors and students during the data analytics component of several courses by demonstrating and presenting statistical analysis and trend analysis in Excel and Tableau. Utilizing Random Forests in the Analysis of Diabetic Data (Graduate Project with Taisir, R.) Sep 2016 – Dec 2016 Statistical Learning (STAT*6801), University of Guelph Guelph, ON

Implemented classification and regression trees in random forests (using boosting/bagging) on diabetic data.

Performed imputation techniques to resolve missing data and determined best variables for classification. Statistical Research Analyst Jun 2013 – Aug 2013

Ontario Council of Agencies Serving Immigrants (OCASI) Toronto, ON

Conducted statistical research related to social dynamics and public policy at a non-profit organization.

Analyzed sample data collected from a survey addressing the needs of a target population.

Cleaned data and performed statistical tests of significance to assist in answering research questions.

Prepared professional reports with summaries and worked closely with policy coordinator to make recommendations to the provincial government based on our analysis. Statistical Consultant Jan 2013 – Apr 2013

Datassist (Care of York University practicum) Toronto, ON

Assisted an organization on a project involving micro financing and social development.

Determined whether a community in a large region was benefiting financially and developing.

Analyzed complicated longitudinal data with advanced statistical techniques (linear mixed-effect models).

Developed models that were relevant and interpretable using domain level knowledge from client.

Cleaned data, merged data sets and performed statistical analysis using various statistical software.

Created graphical and numerical summaries of data, prepared detailed final reports for client and organizations funding the project and presented results to the client. EDUCATION AND ACCREDICATION

PhD in Applied Statistics (Advisors: Dr. Peter Kim, Dr. Tony Desmond) Sep 2016 – Sep 2020 University of Guelph Guelph, ON

GPA: 4.0/4.0 Ontario Graduate Scholarships (Selective) Deans’ Scholarships Google Cloud grant International High Performance Computer Summer School Scholarship, Czech Republic (Highly Selective) MA in Applied Statistics (Part-time) Sep 2011 – May 2015 York University Toronto, ON

GPA: 3.65/4.0 Ontario Graduate Scholarship (Selective) Graduate Scholarship Entrance Award MSc in Applied Mathematics Sep 2008 – Aug 2010

University of Guelph Guelph, ON

GPA: 3.93/4.0 Deans’ Scholarship Fields Institute Award BSc (with Honours) in Mathematics and Statistics Sep 2003 – May 2007 University of Toronto Toronto, ON

Upper year GPA: 3.37/4.0 Double majors Honour Roll for Mathematics Associate Statistician (AStat) Accredited Jul 2019 Statistical Society of Canada

SELECTED COMPUTER SKILLS

Statistics/Data Analytics : SAS, R, SPSS, Stata, MATLAB, Mathematica

Databases : Transact-SQL, MySQL, Microsoft SQL Server

Scripting Languages : Bash, JavaScript, macOS Terminal, Linux (Ubuntu/Debian/Manjaro) Terminal

General Purpose : Python, Java, C++

Version Control : Git (GitHub, BitBucket)

Data Visualization : Tableau, Power BI,

Other : Cloud computing through SSH (Azure, Google Cloud, AWS, XSEDE), ArcGIS

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