OLAIDE YUSUF

Frisco Texas

470-***-****

adyts5@r.postjobfree.com

PROFESSIONAL EXPERIENCE:

* ***** *********** **** ********* with a proven track record of leveraging advanced analytics and machine learning techniques to drive actionable insights and deliver tangible business outcomes. Skilled in manipulating and analyzing large complex datasets, creating predictive models, and building scalable data pipelines. Proficient in programming languages such as Python and R, as well as utilizing tools such as SQL, TensorFlow, and Tableau. Strong communication and collaboration abilities, with a demonstrated ability to translate complex technical concepts into easily understandable insights for both technical and non-technical stakeholders. Passionate about leveraging data to solve real-world problems and drive data-driven decision-making.

Skills

Databases

MySQL, Postgre SQL, Oracle, HBase, Amazon Redshift, MS SQL Server 2016/2014/2012/2008 R2/2008, Tarada

Statistical Methods

Hypothetical Testing, ANOVA, Time Series, Confidence Intervals, Bayes Law, Principal Component Analysis (PCA), Dimensionality Reduction, Cross-Validation, Auto-correlation

Machine Learning

Regression analysis, Bayesian Method, Decision Tree, Random Forests, Support Vector Machine, Neural Network, Sentiment Analysis, K-Means Clustering, KNN and Ensemble Method, Natural Language Processing (NLP)

Hadoop Ecosystem

Hadoop 2.x, Spark 2.x, MapReduce, Hive, HDFS, Sqoop, Flum

Reporting Tools

Tableau Suite of Tools 10.x, 9.x, 8.x which includes Desktop, Server and Online, Server Reporting Services(SSRS)

Data Visualization

Tableau, MatPlotLib, Seaborn, ggplot2

Languages

Python (2.x/3.x), R, SAS, SQL, T-SQL

Operating Systems

PowerShell, UNIX/UNIX Shell Scripting (via PuTTY client), Linux and Windows

Data Scientist August 2019- Till Present

BANK OF AMERICA

Collaborated with data engineers and operation team to implement ETL process, wrote and optimized SQL queries to perform data extraction to fit the analytical requirements.

Performed data analysis by using Hive to retrieve the data from Hadoop cluster, SQL to retrieve data from RedShift.

Explored and analyzed the customer specific features by using Spark SQL.

Performed univariate and multivariate analysis on the data to identify any underlying pattern in the data and associations between the variables. Performed data imputation using Scikit-learn package in Python.

Participated in features engineering such as feature intersection generating, feature normalize and label encoding with Scikitlearn preprocessing.

Used Python 3.X (numpy, scipy, pandas, scikit-learn, seaborn) and Spark 2.0 (PySpark, MLlib) to develop variety of models and algorithms for analytic purposes.

Developed and implemented predictive models using machine learning algorithms such as linear regression, classification, multivariate regression, Naive Bayes, Random Forests, K-means clustering, KNN, PCA and regularization for data analysis.

Conducted analysis on assessing customer consuming behaviors and discovering value of customers with RMF analysis; applied customer segmentation with clustering algorithms such as K-Means Clustering and Hierarchical Clustering.

Built regression models include Lasso, Ridge, SVR, XGboost to predict Customer Life Time Value.

Built classification models include: Logistic Regression, SVM, Decision Tree, Random Forest to predict Customer Churn Rate

Used F-Score, AUC/ROC, Confusion Matrix, MAE, RMSE to evaluate different Model performance.

Designed and implemented recommender systems which utilized Collaborative filtering techniques to recommend course for different customers and deployed to AWS EMR cluster

Involved setting up NPM (node package manager) installation to manage modules.

Utilized natural language processing (NLP) techniques to Optimized Customer Satisfaction.

Designed rich data visualizations to model data into human-readable form with Tableau and Matplotlib

T-MOBILE

Data Scientist Feb 2016- Jul 2019

Led data science projects for clients, delivering predictive models and data-driven recommendations that generated revenue.

Developed and deployed machine learning models for image and text classification, customer segmentation, and predictive maintenance using Python, R, and SQL.

Conducted data cleaning and pre-processing on large datasets using Pandas, NumPy, and other data manipulation libraries.

Built interactive dashboards and visualizations using Tableau, PowerBI, Excel, matplotlib, and Seaborn to communicate insights to stakeholders.

Collaborated with cross-functional teams to translate business requirements into data-driven solutions, managing stakeholder expectations and communicating project progress.

Conducted exploratory data analysis on large datasets using Python and SQL, identifying trends and patterns to inform business decisions.

Built predictive models using regression, classification, and clustering algorithms to forecast sales, customer behavior, and product demand.

Deployed models using cloud platforms such as AWS, GCP, and Azure, integrating with production systems for real-time decision-making.

Developed custom data pipelines using Hadoop, Spark, and NoSQL databases to process and store large volumes of data.

Communicated findings and insights to stakeholders using visualizations and reports, collaborating with cross-functional teams to identify opportunities for improvement.

EDUCATION

Louisiana State University Shreveport

MBA Business Administration

Certification:

Google Cloud Certified

IBM Certified Data Scientist

SAS Certified Data Scientist

Certified Analytics Professional (CAP)

Microsoft Certified: Azure AI Engineer Associate

University of Alabama at Birmingham

BSc Marketing

Mississippi Gulfcoast Community College

AA Business (General)

CERTIFICATION

Certified Systems Administrator (CSA),

ITIL

Certified Scrum Master (CSM)

HONORS AND AWARDS

All America Soccer Team

Most Valuable Player

NJCAA Region 23 Team

Who is Who Among Universities and Colleges

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