Deep Learning
Tolulope Adeyina
Data Scientist
El Paso,UT
Summary
Meticulous Data Scientist accomplished in compiling, transforming and analyzing complex information through software. Expert in machine learning and large dataset management. Demonstrated success in identifying relationships and building solutions.
Overview
3
3
years of professional experience
13
13
years of post-secondary education
4
4
Certifications
Work History
PhD Data Science Intern-Quant|Applied ML
Capital one
Mc lean, VA, United States
06.2023 - 08.2023
- Led a project to evaluate and implement techniques for model error reduction to improve predictive performance within the Account Level Loss Model (ALLM) and Account Level Balance Model (ALBM) at Capital One.
- Analyzed a big dataset of approximately 2 billion records using data science tools like Kubeflow (Enterprise Model Platform),databrick, Snowflake, and GitHub to assess model performance, and python libraries such as Dask for parallel and distributed computing, Apache Spark, Scikit-Learn, .
- Implemented a Generalized additive model, with discrete time logistic hazard model as the base model and Light GBM for the additive function.
- Conducted comprehensive backtesting to rigorously evaluate the effectiveness of model error reduction techniques across diverse economic cycles and scenarios.
- Collaborated with a multi-disciplinary team to design, implement, and test techniques for model error reduction, showcasing strong teamwork and project management skills.
- Created data visualization graphics, translating complex results into comprehensive visual representations using goggle sheets, goggle slides and Excel to the customer credit risk management team.
- Collaborated with business partners to understand business objectives.
- Took notes during meetings to better understand project initiatives and to distribute to stakeholders.
- Brainstormed with data personnel to define data modeling standards and data governance for projects.
Data Science Research Intern
College Of Sciences, University Of Texas At El Pas
ELPASO, United States
06.2022 - Current
- Interviewed or administered standardized tests to research subjects to collect data.
- Compiled, cleaned and manipulated data of about 6 million observations for proper handling.
- Modeled predictions with feature selection algorithms for dimension reduction using Python.
- Modeled food and housing security survey data using logistic regression and decision tree to find out sub-population of students who are at risk and significant prediction of food and housing security. I also considered the interactions and the effects on the dependent variable.
- Tested and validated models for accuracy of predictions in outcomes of interest.
- Developed polished visualizations using ggplots and Tableau, with similar presentation on Power Bi to share results of data analyses.
- Ran statistical analyses within R and Python software to process large datasets, ranging from 6 million observations to 300,000 observations.
- Managed, prepared and manipulated extensive databases using SQL.
- Presented findings orally and in writing with advanced mathematical models using powerpoint.
Graduate Research Assistant
University of Texas
El Paso, United States
05.2020 - Current
- Researched information regarding palindromes in RNA viruses to assist professors with academic pursuits.
- Prepared materials for reports, presentations and submission to peer-reviewed journal publications.
- Gathered, reviewed and summarized literature from scientific journals such as SciFinder and PubMed.
- Used Python to parse GenBank, Fasta files, and Emboss palindrome outputs
- Created pipelines with Python for generation of data from GenBank , and Emboss Palindrome’s website, with output that is statistically analyzed using R
- Analyzed Covid_19 data and RNA-seq data using Python
- Used Pyvcf to extract and analyze data from VCF files.
Bioinformatics Intern
Texas Tech University Health Science Center
El Paso, United States
10.2021 - 12.2021
- Analyzed RNA-Seq data with information of patient divided into 4 groups which are Type 1 diabetics, Type II diabetics, idiopathic and Control.
- Programmed algorithms to Identify diseased pathways of both down regulated and up regulated genes associated with gastro-intestinal diseases using QIAGEN Ingenuity Pathway Analysis (IPA)
- Predicted downstream effect and identified new target/candidate biomarkers using Ingenuity Pathway Analysis (IPA)s.
- Investigated and implemented strategies for modeling and predicting clinical outcomes.
- Performed accurate quantitative analysis of targeted data research, collection and report preparation.
Education
Ph.D. - Data Science
The University of Texas At El Paso
El Paso, TX 08.2021 - 05.2024
Master of Science - Bioinformatics
University of Texas
El Paso, TX 08.2019 - 12.2021
Master of Science - Statistics
University of Ibadan
Ibadan 01.2016 - 07.2019
Bachelor of Science - Statistics
University of Agriculture Abeokuta
Abeokuta 05.2008 - 07.2012
Skills
Python
Research Experience
- Applied the random forest classifier to model the "All of Us Research Data"(NIH) with the goal of identifying the most significant factor impacting vaccination among Hispanic populations. The objective of this project was to utilize the research findings to aid in eradicating cervical cancer through the application of HPV vaccination. (Advisor; Dr. Amy Wagler, 2023).
- Breast cancer histopathology image classification using Deep learning.(2022).
- Anchoring OCR(optical character recognition) on SLAM (Simultaneous localization and mapping) for indoor mapping in health facilities.(Dr Pokojovy,2022)
- Modelling food and housing security survey data using logistic regression and decision tree with a focus students from University of Texas at El Paso. (Advisor; Dr. Amy Wagler, 2022) .
- Comparison of various supervised learning algorithms for multivariate highdimentional Gastroparesis' RNAseq data with about 1600 variables( Internship 2021), and reduced it using PCA, parametric two-sample t test or the nonparametric Wilcoxon rank-sum test, to four genes.
- Developing Python algorithm for mining information from about 50,000 sequences, analyzing and the predicting the occurrence of Palindromes in RNA-viruses. (Dr Ming-Ying Leung, Dr Jonathan Mohl)
- Sentimental analysis of the effect of about 750,000 tweets from the year 2016-2021 related to "cancel culture" and revenues of ten companies using Natural language processing ( presented at Data science for all conference 2021).
- Hierarchical clustering of prostate cancer variant genes to explain the relationships of the genes (Postgenomics, 2020) .
- Mathematical modelling of the transmission dynamic of Lassa Fever (Advisor; Dr. Oluwafemi Oyamakin 2016).
Relevant Modules: Bioinformatics, Post-genomics,Statistical Data mining, Multivariate statistical method for high dimensional data, Mathematical statistics, Statistics in Research(Regression model analysis), Statistical programming(using R, PYTHON,JULIA), Database management(MySQL, SQL), Mathematics for data science, Machine Learning,Data Structure.Building End-End Vision application(CoRise).
Interests
Computer Vision
Natural language Processing
Machine Learning
Graph Theory
Affiliations
- American Mathematical Society
- Society for Industrial and Applied Mathematics
- kagglex bipoc mentorship program
- United Nations Major group from child and youth
- International society for computational biology
Certification
Neural Networks and Convolutional Neural Networks Essential Training
Extra Curricular Activities
1. Position: Collegiate Senator for Graduate Students( 2020 till present).
Organization : Student Government Association (University of Texas at El Paso)
2. Position: President (2021- present)
Organization : African Student Organization
3. Position: Financial Secretary (2022 till present)
Organization : American Mathematical Society
Timeline
PhD Data Science Intern-Quant|Applied ML
Capital one
06.2023 - 08.2023
GitHub for Data Scientists
09-2022
Neural Networks and Convolutional Neural Networks Essential Training
07-2022
Data Science Research Intern
College Of Sciences, University Of Texas At El Pas
06.2022 - Current
LinkedIn logo Building Deep Learning Applications with Keras 2.0
06-2022
Bioinformatics Intern
Texas Tech University Health Science Center
10.2021 - 12.2021
Ph.D. - Data Science
The University of Texas At El Paso
08.2021 - 05.2024
Data analytics certificate -University of Texas at El Paso
12-2020
Graduate Research Assistant
University of Texas
05.2020 - Current
Master of Science - Bioinformatics
University of Texas
08.2019 - 12.2021
Master of Science - Statistics
University of Ibadan
01.2016 - 07.2019
Bachelor of Science - Statistics
University of Agriculture Abeokuta
05.2008 - 07.2012
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