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
