Hello, my name is

Paul London

Biotech Data Scientist

Translating biology into data-driven insights

About me

I’m Paul London, a molecular technologist and data scientist who combines hands-on laboratory expertise with computational and machine learning skills to turn complex biological data into meaningful insights and practical solutions.

I solve biotech problems with data

I’m Paul London, a molecular technologist and data scientist who combines hands-on laboratory experience with computational and machine learning expertise. I build reproducible pipelines and data-driven solutions that bridge biology, technology, and real-world problem solving.

My work sits at the intersection of biotechnology, data science, and AI. With 6+ years of laboratory experience, I apply machine learning, bioinformatics, and data analytics to transform complex scientific and business data into useful insights. I’m particularly interested in genomics, NGS, and AI-driven approaches to biological data, with an emphasis on building practical, scalable solutions and communicating technical results clearly to both scientific and non-scientific audiences.

What I do

I turn complex scientific and business challenges into practical, data-driven solutions. From defining the problem and developing an approach to building and delivering the final solution, I combine technical expertise with clear communication at every stage.

Bioinformatics & Genomics

I apply computational methods to biological and genomic data, building reproducible workflows for NGS, sequencing analysis, and other complex datasets.

Data Science & Analytics

I transform complex scientific and business data through data wrangling, statistical analysis, visualization, and predictive modeling to uncover useful insights.

AI & Machine Learning

I apply AI and machine learning to classification, prediction, automation, and pattern recognition—developing practical solutions to complex problems.

Skills

NGS & Genomics

Next-generation sequencing, library preparation, genomic workflows, variant analysis, single-cell and spatial genomics, and sequencing data analysis.

Bioinformatics

Reproducible computational workflows for processing, analyzing, and interpreting biological data using tools such as GATK, BWA, SAMtools, and BEDTools.

Python and Data Analysis

Python-based data processing, automation, statistical analysis, and scientific computing using tools such as pandas, NumPy, and Biopython.

Machine Learning & AI

Applied machine learning for classification, prediction, pattern recognition, and biological data analysis, including modern AI and LLM-based approaches..

Data Visualization

Clear, informative visualization of complex datasets using Python and other analytical tools to communicate patterns, trends, and results.

Workflow Automation

Automated and reproducible pipelines using Python, Bash, Snakemake, and workflow-oriented tools to improve efficiency, consistency, and scalability.

Molecular Biology & Laboratory Science

Hands-on experience with molecular biology, nucleic acid extraction, PCR, sequencing workflows, assay optimization, and laboratory troubleshooting.

Experience

2026-Present

Moffitt Cancer Center