Davies

Data Scientist DAVIES OBIEKEA - |-https://www.linkedin.com/in/davies-obiekea-0aa791b/ 4, Vitus Okpala Street, Ajao Estate, Lagos, Nigeria. Lagos 100263 https://davies-cv.s3.amazonaws.com/index.html Skills Programming Languages: Python, R Natural Language Processing: NLTK, Spacy Data Manipulation: Pandas, Numpy Data Visualization: Matplotlib, Seaborn Machine Learning: Scikit-learn, TensorFlow, Keras Database and SQL: MySQL, MongoDB Deep Learning: Neural Networks, Other Tools: Tableau Convoluted Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Long Short-Term Memory (LSTM) Projects (Certification project) T E R M DE POSI T S UBS CR I PT I ON – School Capstone Project 2023/2024 ● Utilized Python to analyze about 8000 low-income customers for a bank’s term deposit campaign ● Aggregated and visualized the data by using modules like Pandas, Seaborn and Matplotlib to gain insights. ● Performed Feature Engineering and Feature Selection using Scikit-learn to highlight most pertinent features and then built a Machine Learning Classification model to perform Predictive analysis. ● Built a Flask application and then using Putty and creating an EC2 instance I deployed the model among other cloud computing activities Work Experience DAT A S CI E NT I S T /CONS UME R I NT E L IG E NCE – Niche CX Consulting Firm – Lagos State, Nigeria April 2025 Niche CX Consulting Firm is Africa’s leading integrated customer experience (CX) management service and product provider . • I prepared the 2024/2025 State of CX in Africa Report. Spearheaded end-to-end data preparation, cleaning, and structuring for survey responses from 1,040+ respondents across 20 African countries. • Conducted statistical analysis and trend identification on key CX dimensions including customer expectations, behaviour, service quality, and brand perception. • Developed journey maps, maturity models, and industry benchmarks using metrics such as NPS, CSAT, and support satisfaction. • Synthesized qualitative and quantitative insights into actionable findings, supporting strategic recommendations for CX improvement across sectors. • Produced final report visuals and executive summaries for stakeholder presentation and publication. T R P AND G R P PR E DI CT IV E MODE LL I NG – Personal Project – March 2025 • Developed a two-stage machine learning pipeline to predict Target Rating Points (TRP) and Gross Rating Points (GRP) using ad spend and broadcast metadata. • Performed extensive data preprocessing, log transformation, and feature engineering to reduce skewness and improve model accuracy. • Built and tuned Random Forest Regressor and XGBoost models with hyperparameter optimization using HalvingRandomSearchCV, achieving R² > 0.87 for GRP prediction. • Conducted residual diagnostics, applied sample weighting to address under-prediction of high GRPs, and benchmarked classical vs. ensemble models. • Delivered interpretable insights on ad effectiveness, enabling budget-to-impact estimation and media planning optimization. Education BS C. L I BR AR Y AND I NFOR MAT I ON S CI E NCE – DELTA STATE UNIVERSITY – DELTA STATE, NIGERIA MARCH 2005 FUL L S T ACK DAT A S CI E NCE PR OG R AM CE RT I FI CAT ION - D IGIT AL R E GE N E SY S B U SIN E SS SCH O O L AP R IL 2024 AI PY T HON FOR BE G I NNE RS – COU R SE R A (FRE E O N LIN E N ON -CE R T IFICAT IO N OP T ION CO UR SE ) J AN U AR Y 2025