+447901364528 | imonikheayeni@gmail.com | United Kingdom | LinkedIn | Website | GitHub
Summary
Data Scientist with 7+ years of experience in financial services and predictive analytics. Expertise in developing and deploying machine learning models, conducting statistical analysis, and extracting actionable insights from complex datasets. Proficient in Python, SQL, and cloud technologies (Azure). Strong background in predictive modeling, deep learning, and natural language processing. Skilled in translating business problems into data-driven solutions and communicating technical findings to diverse stakeholders. Holds an MSc in Data Science with distinction, Microsoft Certifications in Power BI & Azure AI, along with IT Specialist Certifications in Databases & Data Analytics.
TECHNICAL SKILLS
SQL & Programming : Advanced SQL (writing efficient, performant queries), Python (Pandas, NumPy, Matplotlib, Scikit-learn)
Data Visualization : Microsoft Power BI (Certified), Tableau, Matplotlib, Seaborn, Looker
Business Intelligence : Dashboard creation, KPI development, metrics design, Advanced DAX
Data Analysis : Statistical analysis, predictive modeling, pattern recognition
Database Systems : Experience with databases (Certified), Microsoft Azure (Certified), Snowflake, AWS (Currently preparing for Solutions Architect Associate)
Cloud Platforms: Microsoft Azure, AWS (Currently preparing for Solutions Architect Associate), Snowflake
EDUCATION
Master of Science in Data Science (Distinction) | Cardiff Metropolitan University - Cardiff, United Kingdom. May 2024. Link
Master of Science in Geography and Planning | University of Lagos - Lagos, Nigeria. March 2018. Link
Bachelor of Science in Geography and Regional Planning (2.1) | University of Benin - Benin City, Nigeria. Link
CERTIFICATIONS
Microsoft Certified Power BI Data Analyst Associate (Obtained March 2025) Link
Certiport Certified IT Specialist in Databases (Obtained May 2025) Link
Certiport Certified IT Specialist in Data Analytics (Obtained April 2025) Link
Certified Power BI Report Designer, Cardiff Metropolitan University (Obtained May 2025) Link
Microsoft Certified: Azure AI Fundamentals (Obtained May 2024) Link
Applied Data Science Lab, WorldQuant University (Completed January 2025) Link
Currently Pursuing: AWS Certified Solutions Architect Associate ( Completion by July 2025)
Planned for Future: Microsoft Certified: Azure Data Engineer Associate (DP-203)
Planned for Future: Snowflake SnowPro Core Certification
PROFESSIONAL EXPERIENCE
Cardiff Metropolitan University - Cardiff, United Kingdom Research Analyst / Assistant (05/2023 - Present)
Orchestrated data analysis for Digital Technology Learning Support Network (DTLSN) Project in Wales, streamlining data ETL, data modelling, and data visualization using Python libraries (NumPy, Pandas, Matplotlib, Seaborn, Scikit Learn), Power BI, and Tableau, for enhanced efficiency and accuracy.
Implemented machine learning models for various research projects, focusing on predictive analytics.
Conducted advanced data analysis using qualitative and quantitative coding (NVivo, Python), statistical analyses (SPSS, Python), and data visualisation (Tableau, Power BI, Python).
Access Bank Plc - Lagos, Nigeria
Data and Insight Analyst (04/2019 - 01/2023)
Developed and maintained reports, dashboards, and KPIs using SQL and Python, improving operational efficiency.
Built predictive models to analyze risk asset performance and optimize pricing strategies, thus helping to maximize profit.
Implemented data-driven solutions to reduce loan delinquency, collaborating with stakeholders to develop action plans.
Conducted in-depth analysis of marketing campaigns using Python and SQL, evaluating ROI and impact on customer metrics.
Conducted A/B testing for marketing campaigns, analysing statistical significance and ROI.
Diamond Bank Plc -
Customer Experience Analyst (04/2014 - 03/2019)
Transformed raw transaction data into meaningful insights using SQL and Excel.
Developed and executed micro-segmented marketing campaigns targeting dormant customers, resulting in increased monthly revenue generation.
Leveraged Relational/Statistical Database Management Systems (RDBMS) to perform data analytics and enhance online marketing activities, achieving a productivity increase of over 90% through effective data mining, modeling, and SQL script writing.
Utilized customer segmentation models to profile usage patterns and tenure, enabling targeted offer mapping and personalized campaign strategies.
Collaborated with stakeholders to understand business requirements and translate them into analytical solutions.
Created data visualization dashboards that improved decision-making processes.
KEY PROJECTS
Airbnb Predictive Pricing Model (Python, Random Forest, Ridge Regression): Developed machine learning models to predict Airbnb prices with 58.6% R² accuracy, implementing feature engineering techniques and ensemble methods to optimize model performance. Link
Stock Volatility Analysis & Forecasting (Python, GARCH, EGARCH): Conducted comparative volatility analysis of MSFT vs. AAPL, identifying Apple as more volatile. Built and validated GARCH and EGARCH models for Microsoft, demonstrating volatility clustering, persistence, and a significant "leverage effect" for enhanced risk prediction. Link
Stroke Risk Prediction Model (Python, Machine Learning, Flask, GIT, Heroku): Built and deployed a stroke risk prediction model using machine learning algorithms, featuring automated model retraining pipeline and interactive user interface. Link
Geospatial Machine Learning (Python, GeoSpatial Libraries): Implemented spatial clustering algorithms to analyze geographic patterns in customer data, uncovering key location-based trends that informed strategic business decisions. Link
NLP, Sentiment & Business Impact Analysis (Python, NLTK, SpaCy): Developed a sentiment analysis pipeline to assess the business impact of global events using natural language processing techniques, achieving 87% accuracy in sentiment classification. Link