• Produced complex SQL queries to calculate aggregate figures linked to client data quality, highlighting relevant focus areas. • Conducted large-scale data processing using Python and Spark, leading to an increase in usable customer data. • Presented exploratory data analysis results to senior internal and external stakeholders, providing detailed insights into business operations. • Designed and maintained Power BI dashboard solution, showcasing KPIs associated with customer demographics data. • Architected AWS and Databricks solution to enable simple extraction of analysis results. • Operated with a cross-functional agile team, consistently completing 2-week sprints and engaging in scrum ceremonies. • Utilised JIRA to create epics and associated tickets, documenting work within Confluence pages.

SciBite | Sep 2019 - Jun 2022

Data Scientist

• Consistently created reusable Python scripts for clients, transforming JSON and XML data using NLP techniques (Named Entity Recognition, Regular Expressions, Topic Modelling, etc.) • Engineered an AWS ETL data pipeline to process unstructured data from multiple sources, ingesting clean data into SQL databases and Neo4j knowledge graphs. • Utilised SciKit-Learn to produce clustering algorithms, identifying relevant journal focus areas for key clients. • Contributed to the conversion of proof-of-concepts into full licenses, resulting in a 9% increase in company annual revenue.

My Education

Take a look at my formal education

Master of Science - MS, BioinformaticsQueen Mary University of London | 2019

Bachelor of Science - BS, BiochemistryQueen Mary University of London | 2018

King Edward VI Grammar School | 2015

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