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Work Background
CoinListSenior Data Scientist
Sep. 2024- Leverage LLM and fraud rules for fraud detection. - Build dashboards in mode analytics to monitor performance of digital products, such as, fiat on-ramp, staking etc. - Carry out data-driven research to better understand business opportunities and performance. - Build data models, including fact accumulating models, using dbt and snowflake, easing analytics.
PwC CanadaExperienced Associate - Software Development
Sep. 2023 - Sep. 2024Calgary, Alberta, Canada- Designed and developed software solutions using JavaScript, Apex, and Visualforce for Public Service clients, delivering tailored applications to meet business needs.
- Built ETL pipeline using SFDMU and automate business processes using apex triggers and flows.
- Implemented CI/CD pipelines for automated code validation and deployment, leveraging Azure DevOps and Salesforce CLI to ensure smooth delivery and efficient version control.
izifinData Scientist
Sep. 2021 - Sep. 2023- Led the development of credit risk models, applying predictive analytics and machine learning to optimize digital loan underwriting for both SME and retail segments, improving portfolio performance and reducing defaults.
- Built a a KYC verification system using one-shot learning for speaker authentication, strengthening fraud prevention measures and improving customer verification processes.
- Enhanced credit decisioning strategies by determining optimal credit value based on the firm’s risk appetite, customer debt-to-income (DTI) ratios, cash flow patterns, and other key risk indicators, ensuring responsible lending and sustainable growth.
CarbonData Scientist
May. 2019 - Aug. 2021Remote- Designed, deployed, and continuously optimized both application and behavioral credit risk scorecards, reducing default rates.
- Developed a Customer Lifetime Value (CLTV) model to identify high-value customers early in their lifecycle, enabling smarter loan sizing decisions and boosting total disbursement values.
- Improved customer retention and engagement by executing A/B tested SMS marketing campaigns and rolling out a data-driven segmentation framework powered by lifetime value predictions and behavioural analysis. - Worked on fraud prevention initiatives by developing dynamic fraud rules and leveraging Neo4j to detect fraud rings, identifying linked entities through IP address similarities and geolocation patterns—effectively mitigating lending-related fraud exposure.
- Validated and stress-tested credit risk models using Out-of-Time (OOT) datasets and Gini index analysis to ensure long-term predictive stability.
- Built and maintained interactive KPI and transaction monitoring dashboards using Tableau and Google Data Studio, delivering real-time insights into the performance of lending and non-lending products.
Sterling Bank PlcData Scientist
Feb. 2019 - May. 2019Marina, Lagos- Conducted Business Intelligence analysis using PowerBI to deliver actionable insights and data-driven decisions.
- Developed and managed ETL processes with Microsoft SQL Server Integration Services (SSIS) for seamless data integration.
- Performed data wrangling, preprocessing, and modeling using MS SQL, Python, and Azure ML Studio for various analytical tasks.
- Built machine learning models, including churn prediction and customer complaint analysis, to improve customer retention and satisfaction.
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