Olawale Dosunmu

- Build machine learning models for various use cases including loan decisioning for deployment to production.
- Building a fraud detection system to improve the ability to identify patterns in fraudulent loan applications and prevent
future occurrence of similar cases.
- Monitoring of all risk indicators in production to ensure all metrics are trending according to expectations and to immediately
spot any deviations for a fix.

Build machine learning models for various use cases including loan decisioning for deployment to production.
Building a fraud detection system to improve the ability to identify patterns in fraudulent loan applications and prevent future occurrence of similar cases.
Monitoring of all risk indicators in production to ensure all metrics are trending according to expectations and to immediately spot any deviations for a fix.

Built and deployed into production Credit Default Models for decisioning on loan applicants, as well as Credit Scorecards used in scoring loan applicants based on risk assessment.
Built fraud detection and prevention scorecards to alert underwriters of potentially fraudulent applications.
Built dashboards used in monitoring Model Performance, KPIs, and other important metrics.
Working with the product and acquisition teams to build pipelines for effectively targeting customers while reducing marketing and acquisition costs.
Built a pipeline for reading unstructured data extracted from credit reports to help expand available data points and improve the decisioning system.

Acting as team lead on a project for building credit risk scoring, customer segmentation, customer churn and cross-selling solution for a transnational client that’s present in 33 countries across Africa.
Built a predictive solution that is being deployed in predicting key metrics for a telecommunications firm.
This has so far achieved 23% reduction in cost while boosting revenue by 17%.
Building dashboards and automating reporting processes for various clients, in the process providing real-time analytics to aid in decision making.
Part of a team that implemented on-premise, and cloud custom data warehousing solutions.

Image Search tool that returns similar items from eBay and Amazon to an image uploaded by a user by employing Google Vision API.
Analyzed actigraphy dataset and building machine learning model to accurately predict patient response to treatment during clinical trials.
Part of a team of Data Scientists that works with pre-funding startups to build innovative solutions under the supervision of a senior data scientist.

Reporting projections on future performance of key metrics based on historical data using predictive analytics models.
Estimating the financial impact of projects and working with stakeholders to accurately model the cashflow and working capital requirements through to project completion.
Preparing project bid documents, which involved doing cost analysis, calculating the lifetime value of the project, assessing risk factors that could affect the success of the project.
Successfully doing this resulted in an award of recognition upon completion of a project due to the qualify and timeliness of completion.

Built and deployed into production Credit Default Models for decisioning on loan applicants, as well as Credit Scorecards used in scoring loan applicants based on risk assessment.
Built fraud detection and prevention scorecards to alert underwriters of potentially fraudulent applications.
Built dashboards used in monitoring Model Performance, KPIs, and other important metrics.
Working with the product and acquisition teams to build pipelines for effectively targeting customers while reducing marketing and acquisition costs.
Built a pipeline for reading unstructured data extracted from credit reports to help expand available data points and improve the decisioning system.

Acting as team lead on a project for building credit risk scoring, customer segmentation, customer churn and cross-selling solution for a transnational client that’s present in 33 countries across Africa.
Built a predictive solution that is being deployed in predicting key metrics for a telecommunications firm. This has so far achieved 23% reduction in cost while boosting revenue by 17%.
Building dashboards and automating reporting processes for various clients, in the process providing real-time analytics to aid in decision making.
Part of a team that implemented on-premise, and cloud custom data warehousing solutions.

Image Search tool that returns similar items from eBay and Amazon to an image uploaded by a user by employing Google Vision API.
Analyzed actigraphy dataset and building machine learning model to accurately predict patient response to treatment during clinical trials.
Part of a team of Data Scientists that works with pre-funding startups to build innovative solutions under the supervision of a senior data scientist.

Reporting projections on future performance of key metrics based on historical data using predictive analytics models.
Estimating the financial impact of projects and working with stakeholders to accurately model the cashflow and working capital requirements through to project completion.
Preparing project bid documents, which involved doing cost analysis, calculating the lifetime value of the project, assessing risk factors that could affect the success of the project. Successfully doing this resulted in an award of recognition upon completion of a project due to the qualify and timeliness of completion.