Toheeb Olaniyan
Katy,United States
Summary
Dynamic data science professional with extensive hands-on experience in developing machine learning algorithms and statistical models. Expertise in building robust predictive models using techniques such as logistic regression, decision trees, and support vector machines, complemented by proficiency in data balancing methods like SMOTE. Skilled in managing end-to-end data science workflows, including data preprocessing, feature engineering, model training, and performance evaluation. A strong foundation in financial data analysis facilitates the translation of complex datasets into actionable insights that drive strategic business decisions.
Overview
11
11
years of professional experience
1
1
Certification
Work History
Business Analyst
Empower Retirement
06.2022 - Current
- Developed predictive models using logistic regression and decision trees to analyze customer financial behavior patterns, improving recommendation accuracy by identifying high-value client segments
- Applied SMOTE techniques to address class imbalance in customer datasets, enhancing model performance for minority class prediction (loan default risk assessment)
- Built and deployed machine learning pipelines in Python to automate customer segmentation, reducing manual analysis time and improving targeting precision
- Created interactive Tableau dashboards incorporating model outputs to visualize customer risk scores and behavioral predictions for stakeholder decision-making
- Implemented SVM classifiers to categorize customer financial wellness profiles, supporting personalized service recommendations
- Collaborated with compliance teams using statistical analysis to identify high-risk cases, achieving 25% improvement in fraud detection accuracy
- Conducted A/B testing on financial product recommendations, analyzing results using statistical significance testing and confidence intervals
Combat Engineer / Team Leader
U.S. Army National Guard
01.2022 - Current
- Security Clearance: Active Secret Security Clearance
- Applied data-driven risk assessment models for route clearance operations, utilizing real-time data analysis and statistical modeling for mission planning
- Implemented systematic problem-solving approaches and analytical thinking in high-pressure environments
- Led cross-functional teams and demonstrated strong communication skills in translating complex analytical findings into actionable strategies
Data Analyst
TipTop Capital
05.2021 - 04.2022
- Built predictive models using logistic regression and decision trees to analyze customer creditworthiness and loan default risk, achieving 82% model accuracy
- Performed comprehensive data analysis on customer databases using Python and SQL to identify key features influencing loan approval decisions
- Applied feature engineering techniques to transform raw customer data into meaningful predictive variables for machine learning models
- Conducted statistical analysis and hypothesis testing to validate model assumptions and ensure robust risk assessment frameworks
- Created data visualizations using Tableau and Python (Matplotlib/Seaborn) to communicate analytical findings and model performance to stakeholders
- Implemented data quality control processes to clean and preprocess customer datasets, ensuring high-quality inputs for modeling workflows
Junior Data Analyst
MCL Capital
06.2018 - 02.2021
- Developed machine learning models to predict real estate investment performance using decision trees and ensemble methods, supporting $2M+ investment decisions
- Applied clustering algorithms (K-Means) to segment real estate portfolios based on risk profiles and ROI patterns, identifying optimal investment strategies
- Built automated ETL pipelines using SQL and Python to process large financial datasets (500K+ records), ensuring data quality for model training
- Designed predictive models for cash flow forecasting using regression techniques, achieving 85% accuracy in quarterly predictions
- Implemented feature engineering techniques to create meaningful variables from raw financial data, improving model interpretability for stakeholder presentations
- Conducted statistical analysis and variance detection using Python libraries (Pandas, NumPy) to identify discrepancies in underwriting assumptions
- Created comprehensive data visualizations using Matplotlib and Seaborn to communicate model insights to non-technical stakeholders
Teller / Customer Service Representative
Fidelity Bank PLC
01.2015 - 01.2018
- Applied statistical analysis to customer banking behavior data to identify cross-selling opportunities and product recommendations
- Implemented data quality control processes to identify and resolve discrepancies in daily transaction reports
- Collaborated with team members using data-driven insights to develop strategic initiatives for meeting branch targets
Education
Bachelor of Science - Business Analytics and Data Science
New Jersey City University
New JerseyAssociate degree - Accounting
Federal Polytechnic Ede
Osun State, NigeriaSkills
- Data science proficiency
- Machine learning algorithms
- Data Preprocessing: Feature Engineering, Data Cleaning, SMOTE (Synthetic Minority Oversampling), Outlier Detection
- Model Development: Cross-validation, Hyperparameter Tuning, Model Selection, Performance Evaluation (Precision, Recall, F1-Score, AUC-ROC)
- Programming: Python (Scikit-learn, Pandas, NumPy, Matplotlib, Seaborn), SQL, Jupyter Notebook
- Analytics & Visualization
- Tools: Power BI, Tableau, Excel (Advanced), Statistical Analysis
- Techniques: A/B Testing, Customer Segmentation, Cohort Analysis, Trend Analysis, Statistical Modeling
- Data extraction and ETL expertise
- Business Intelligence
- Reporting: Dashboard Development, KPI Tracking, Ad-hoc Analysis, Automated Reporting
- Communication: Stakeholder Presentations, Technical Documentation, Cross-functional Collaboration
Accomplishments
- Management - Directed marketing team of 12 direct reports.Supervised creation of marketing strategies/plans and ensured operations were within budget constraints.
- Data Organization - Classified, recorded and summarized numerical and financial data to compile and keep financial records.
- Client Interface - Worked in close collaboration with clients, providing accounting, payroll and taxation advice.
- Research and Analysis - Evaluated PeopleSoft accounts receivable detail level mapping to general ledger.
- Consumer Research - Effectively executed new marketing outlines based on market research data collected to reflect consumer interest on both tactical and strategic levels.
- Process Improvement - Achieved revenue objective by implementing cost-cutting measures.
Certification
AWS Certified Solutions Architect
Languages
English
Native or Bilingual
Interests
- Tech enthusiast, passionate about exploring the latest advancements and innovations
- Supporting STEM education initiatives and mentorship programs
- Web Development and Design
- Sustainable Tech Innovations
- Artificial Intelligence (AI) and Machine Learning
- Developing software, websites, and apps in various programming languages
Timeline
Business Analyst
Empower Retirement
06.2022 - Current
Combat Engineer / Team Leader
U.S. Army National Guard
01.2022 - Current
Data Analyst
TipTop Capital
05.2021 - 04.2022
Junior Data Analyst
MCL Capital
06.2018 - 02.2021
Teller / Customer Service Representative
Fidelity Bank PLC
01.2015 - 01.2018
Associate degree - Accounting
Federal Polytechnic Ede
Bachelor of Science - Business Analytics and Data Science
New Jersey City University