MAHESH
DIVAKARAN
Senior Statistical Programmer · Clinical Data Scientist · PhD Candidate
Senior Statistical Programmer and Clinical Data Scientist with close to a decade (9+ years) of experience in clinical data analysis, CDISC standards (SDTM, ADaM), and TLG/TFL generation. Currently a PhD candidate in Statistics at Amity University. Expert in R, SAS, and Python with a strong track record of building R packages, automating clinical reporting pipelines, and developing R Shiny dashboards. International conference presenter (PHUSE US & EU), SAS Certified Base Programmer, and part-time Biostatistics lecturer. Experienced in FDA regulatory submissions and cross-functional team leadership.
Core CompetenciesR (Advanced)Python (Advanced) SAS BaseSAS Macros SAS/STATR Package Dev R ShinyR Markdown
CDISCSDTM ADaMTLG / TFL Define.xmlFDA XML Submissions CSR & SAP Automation
admiralsdtm.oak xportrmetacore rtables
TableauPower BI ggplot2Plotly Survival AnalysisNLP / NER Git / GitHubLaTeX
- Lead R package development and validation for clinical trial reporting workflows
- Maintain and expand an R package catalogue ensuring reproducibility and compliance
- Drive TLG generation using validated R packages aligned with CDISC and regulatory standards
- Led R Shiny dashboard development for clinical data visualization and TFL automation
- Architected and maintained R packages for end-to-end SDTM, ADaM, and TFL creation
- Mentored and trained analysts in open-source clinical reporting tools
- Developed SAS programs for clinical summaries in compliance with CDISC standards
- Developed R Shiny dashboards for clinical data visualization and interactive trial reporting
- Built R packages to automate ADaM dataset generation and SAS date conversion
- Created R Markdown documentation and catalogues for R scripts
- Converted clinical datasets to CDISC/SDTM across multiple therapeutic areas
- Developed SAS macro programs for ADaM and TFL creation
- Generated XML outputs for FDA regulatory submissions
- Conducted COVID-19 data analysis using Lasso and Ridge Regression
- Developed Medical Entity Recognition (Bio-NER) models for insurance data
- Researched cryptocurrency value forecasting using time-series models
- Developed ML models for Pricing Intelligence, Sales Forecasting, and CLTV prediction
- Delivered a webinar on the Buy Till You Die model for CLTV
- Tweet Sentiment Analysis using NLP; contributed to chatbot development (NLU)
- Built regression, classification, and dynamic pricing models
- Taught Biostatistics to medical students covering descriptive statistics, inferential methods, clinical trial design, and data interpretation
| Conference | Location | Year |
|---|---|---|
| PHUSE US Connect 2023 | Orlando, USA | March 2023 |
| PHUSE EU Connect 2022 | Belfast, UK | November 2022 |
| PHUSE EU Connect 2021 | London, UK | November 2021 |
| PSI Conference 2021 | Virtual | October 2021 |
| ISPS Conference 2016 | Aligarh, India | December 2016 |
🏆 Quarterly Employee Award – Genpro Research · NCC B Certificate – NCC India