Hi There, I'm Ime!
A data scientist who loves turning raw data into useful solutions — whether that’s uncovering patterns, building machine learning models, or helping teams make smarter decisions. My work sits at the intersection of analytics and engineering, with a growing focus on MLOps to bridge the gap between experimental models and real-world deployment.
On the technical side, I work with Python (NumPy, Pandas, Scikit-learn, TensorFlow), SQL, and tools like Power BI to handle everything from data wrangling to visualization. I’ve built models for regression, classification, and clustering problems, but I’m just as comfortable explaining the results to non-technical stakeholders as I am fine-tuning the code.
Right now, I’m sharpening my skills in machine learning, deep learning, and MLOps — because great models only matter if they can actually be used. I enjoy collaborating with others, geeking out over data, and constantly learning.
If you’re working on something data-related, let’s chat. I’m always happy to brainstorm ideas or swap lessons learned.
Experience
I solve complex business challenges with data. My work bridges technical execution and and strategic decision-making, delivering measurable impact through analytics.
Currently focused on roles where I can apply advanced Machine Learning techniques and data storytelling to drive innovation and efficiency.
Data Scientist
Darlytics (Remote)
February 2025 - Present
Built and deployed Machine Learning models, improving forecast accuracy by 19%. Designed interactive dashboards (adopted by 5+ teams) that streamlined reporting and reduced ad-hoc data requests by 35%. Through cross-functional collaborations, I contributed to innovations that drove 15% gains in operational efficency.
Data Analyst
Schlumberger, Nigeria
May 2018 - Present
I used tools like MySQL, Python, Excel, and Power BI to analyze data, create dashboards, and drive decision-making. I led teams in developing predictive models to optimize operations and ensure safety, contributing to a 25% reduction in well costs while maintaining data quality and integrity.
Field Technical Analyst
Schlumberger, Nigeria
December 2012 - May 2018
Accurately captured and transmitted surface data for real-time analysis of drilling parameters, ensuring compliance with industry standards. I maintained equipment performance through regular calibration and supervised surface logging operations to collect essential geological data.
Personal Projects
- The datasets, analyses, and reports presented in this portfolio are created solely for demonstration purposes. They do not contain real proprietary, confidential, or sensitive information from any company, institution, or individual. These examples are designed to showcase my technical skills in data science and data analysis while adhering to ethical guidelines and respecting data privacy.
30 Days Data Science Series
Completed a 30-day Machine Learning challenge, covering key concepts from algorithms to deep learning. Explored topics like supervised/unsupervised learning, neural networks, and model optimization, with practical applications.
Superstore Sales Analysis and Prediction
This project analyzes retail sales data to uncover key trends, identify growth opportunities, and provide actionable insights. The goal is to deliver accurate sales forecasts, empowering the organization to make data-driven decisions.
Malware Prediction and Windows Device Clustering
The aim of this project is to predict the probability of a Windows machine being infected by malware. It also groups machines into clusters based on shared characteristics.
Advertising Sales Prediction
In this project, I trained a machine learning model to make sales prediction based on amount spent on TV, radio, and newspaper advertisement.
Iris Dataset Classification
In this project, I trained a machine learning model that can learn from the measurements of the iris species and classify them.
Car Price Prediction
In this project, I trained a machine learning model that can predict the present price of a car using certain features.
What Drives Me
- Currently, I’m focused on:
- Advancing Data Science: Designing machine learning models that drive business innovation.
- Open Source Contributions: Supporting projects that improve the tech ecosystem.
- Continuous Learning: Exploring new frameworks and methodologies to sharpen my expertise.
Technical Skills
Python
MySQL, PostgreSQL, SQLite
Microsoft Excel, Google Sheets
Power BI, Tableau
Slack, Microsoft Teams, Google Meet, Zoom
A Note to My Future Employer
- As a detail-driven data professional with a passion for insights and innovation, I'm excited to take the next step in my career journey. My goal is to become a well-rounded Data Architect, designing and implementing scalable, efficient data systems that drive business growth. To achieve this goal, I'm working at expanding my skill set in data science, machine learning, MLOps, and cloud computing.
- I'm looking for an environment that fosters collaboration, innovation, and continuous learning. I'm excited about the opportunity to work with a team of experienced data professionals, learning from their expertise and sharing my knowledge and insights.
- I'm confident that my strong analytical foundation, combined with my enthusiasm for learning and growth, makes me an ideal candidate for a Data Science role. I look forward to contributing my skills and experience to a progressive organization and taking the next step in my journey to becoming a Data Architect.