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Q&A With Tolulope Adeyina

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Tolulope Adeyina
Data Scientist, Givelify
Location: Indianapolis, IN United States
Joined: Mar 20th, 2025

About (request update)

Education (request update)

The University of Texas At El Paso class of 2025

Undergrad Major: Bioinformatics

Campus Organization:

Givelify

Experience

I currently work with Givelify as Data Scientist
I have 5 years of experience working in the Information Technology industry.

Data Scientist | Givelify
From January 2025 to Current • 1 year(s)
Defined donor consistency metrics, engineered scalable pipelines for $60M+ donations, conducted A/B testing, applied ML modeling with >85% accuracy

Data Scientist | Givelify
From January 2025 to Current • 1 year(s)
Defined donor consistency metrics adopted across Product, Marketing, and Engineering, creating a unified framework to track donor retention. Engineered scalable pipelines and dashboards to analyze $60M+ in annual donation flows. Conducted preliminary analyses and monitored A/B testing for new product features. Applied ML and statistical modeling to forecast donor behavior with >85% accuracy.

Graduate Research Assistant | Building Scholar Research Group(UTEP)
From September 2019 to Current • 7 year(s)
Breast cancer histopathology image classification, developed Python algorithms for mining sequences, analyzed structured and unstructured data

Data Science Lead | Demoscopic Analytics
From December 2022 to December 2024 • 2 year(s)
Directed end-to-end data science projects, conducted A/B testing increasing traffic by 40%, performed sentiment analysis on 750K tweets

Data Science Intern | Microsoft
From June 2024 to August 2024 • 0 year(s)
Built fine-tuned LLM-based topic model, created dynamic dashboards, enhanced Azure OpenAI model performance, deployed RAG chatbot

Data Science Intern | Microsoft
From June 2024 to August 2024 • 0 year(s)
Built a fine-tuned LLM-based topic model (NLP) for real-time detection of concurrent outages that mitigated over $50 million in loss revenue using Kusto Query Language and Python (PySpark). Created dynamic dashboards using Python to visualize outage impacts and customer specific pain points. Enhanced Azure OpenAI model performance for topic representation, achieving an 85% stakeholder validation rate.

PhD Data Science Intern-Quant|Applied ML | Capital One
From June 2023 to August 2023 • 0 year(s)
Led model improvement project reducing error from 10% to 2.7%, analyzed 2 billion records, implemented stacked model with LightGBM

PhD Data Science Intern - Quant|Applied ML | Capital One
From June 2023 to August 2023 • 0 year(s)
Led a model improvement project, reducing error from 10% to 2.7% in Capital One's Account Level Loss and Balance Models (ALLM and ALBM) by implementing advanced error reduction techniques. Analyzed 2 billion records with tools like Kubeflow, Databricks, Snowflake, and Python (Dask, Spark, Scikit-Learn) to optimize model performance. Implemented a stacked model using a logistic hazard model with LightGBM as a meta model.

Data Science Research Intern | College Of Sciences, University Of Texas
From June 2022 to August 2022 • 0 year(s)
Modeled predictive algorithms for NIH project analyzing 6M records, employed feature selection and logistic regression

Bioinformatics Intern | Texas Tech University Health Science Center
From October 2021 to December 2021 • 0 year(s)
Analyzed RNA-Seq data, identified diseased pathways, predicted clinical outcomes using IPA

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