Peter Babalola Eniola
Rietstraat 47, 9000 Ghent, Belgium | - |-| www.linkedin.com/in/petereniola
PROFESSIONAL SUMMARY
Data Analyst with strong proficiency in Python, SQL, and statistical modelling, experienced in automating workflows and generating
actionable insights. Proven track record in enhancing operational efficiency and analyzing time-series data. Brings expertise in
translating complex data into strategic solutions while effectively collaborating with cross-functional teams. Ready to leverage data
science skills in a dynamic, industry-focused environment to drive innovation.
EDUCATION
Ghent University, Belgium & Aarhus University, Denmark
International MSc, Soil and Global Change (IMSOGLO)
Federal University of Technology Akure (FUTA), Nigeria
BSc. (Hons), Agricultural Technology (First Class Hons, Top 1%)
2024 - - 2023
WORK EXPERIENCE
Faculty of Bioscience Engineering, Ghent University
Feb 2025 - Jun 2025
Data Science Intern (Academic Project) Belgium
•Collaborated on a research project to predict the environmental sorption behaviour of Active Pharmaceutical Ingredients (APIs) in soil
and sediment using machine learning models.
Cleaned and structured complex real-world data from over 15 scientific tables and external publications into usable formats (Pandas,
CSV, DataFrames).
•Engineered features from molecular descriptors using Python, RDKit, and SMILES strings; applied dimensionality reduction to
optimize model inputs.
•Built and tuned predictive models (Random Forest, Linear Regression, SVM) to estimate Kd values; validated models using 10-fold
cross-validation. Conducted exploratory data analysis and visualized results using Matplotlib and Seaborn. •Delivered project results in
a Jupyter Notebook with clearly written code, analysis, and interpretation suitable for academic defence.
•Link to projects: https://drive.google.com/drive/folders/1i2u4_Fa0woajjp2dYWpExb72KUCsdkqj?usp=drive_link
Rubber Estate Nigeria Ltd. Nov 2023 - Aug 2024
Data Officer Ogun, Nigeria
•Automated data reporting workflows using Excel, echoing data handling efficiencies found in pandas and enhancing timeliness and
accuracy by 30%.
•Analyzed tapping block productivity, absentee trends, and contract records with SAP and Excel, applying core statistical concepts to
derive actionable insights.
•Generated weekly and monthly reports by integrating SAP, Excel, and SQL queries, supporting strategic decision-making across teams.
TECHNICAL SKILLS
•Modelling & Analytics: HYDRUS-1D, AquaCrop, SoilMapView, R, Python, Excel, MINITAB, Statistical Analysis, Machine Learning,
Data Analysis, Time-Series Data Analysis, seaborn, random forest, SVM
•Python (NumPy, Pandas), Jupyter Notebook, Data Cleaning, Data Visualization (Matplotlib, Seaborn)
•k-Nearest Neighbors (kNN), Linear Regression, Logistic Regression, Model Selection, Regularization (Ridge, Lasso), Decision Trees,
Performance Evaluation Metr
CSV data manipulation, Feature engineering, Label encoding, Scikit-learn basics
•Data Management & Visualization: SAP S4HANA, Tableau, SQL, Data Visualization
•Other Tools: Excel, Word, Powerpoint, Ms Suite, HTML/CSS, AWS, IoT Systems
CERTIFICATIONS
•Google Professional Certificate in Data Analytics, •Fundamentals of AI, Machine Learning, and Python Programming (Packt)
•Applied Statistics Using R : Ghent University
•Advanced Generative Adversarial Networks (GANs), -Deep Learning with Keras and Practical Applications (Packt)
