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Chinonso Okorafor

@chinonsookorafor

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Data Scientist turning complex data into actionable machine-learning insights and dashboards.

United Kingdom

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What I'm looking for

I’m looking for a role where I can build reliable ML and analytics solutions end-to-end—turning messy data into clear dashboards and decisions, collaborating with operations/product, and continuously improving models and data pipelines.

I’m an experienced Data Scientist focused on analyzing complex datasets and delivering actionable insights through statistical analysis and machine learning. I’m proficient in Python and R, with deep expertise in data wrangling, visualization, and communicating results clearly to technical and non-technical audiences.

In my recent work, I’ve conducted correlation analysis to identify key process parameters impacting wafer/chip yield, dissected test-result anomalies to improve reliability and efficiency, and built organization-wide dashboards for real-time KPI visibility. I’ve also delivered end-to-end ML solutions—forecasting critical path process delays (20% supply chain efficiency improvement), predicting customer order quantities with 15 RMSE, and building a defect detection algorithm with 90% accuracy—along with ML tooling such as customized Python libraries and monitoring pipelines.

Experience

Work history, roles, and key accomplishments

Current

Test Data Scientist

Current

Pragmatic Semiconductors

Aug 2023 - Present (2 years 8 months)

Conducted correlation analysis to identify process parameters with the highest impact on wafer/chip yield, enabling data-driven process optimization. Developed organization-wide Python dashboards for real-time KPI visibility and built customized Python libraries to improve wafer/chip-level analysis.

Python Statistical Analysis KPIs Data Wrangling Data Visualization Predictive Analytics

Data Scientist

Seamless Source

Feb 2023 - May 2023 (3 months)

Built and deployed a machine learning model to forecast critical path process delays, improving supply chain efficiency by 20%. Developed forecasting for future order quantities (RMSE 15) and a defect detection algorithm with 90% accuracy to reduce quality control inspection time.

Python Machine Learning Supply Chain Analytics Error Metrics (RMSE)predictive modeling

Data Scientist

Willok Group

Feb 2020 - Oct 2022 (2 years 8 months)

Used historical data and predictive modeling to forecast project completion dates, enabling proactive planning and improved delivery. Performed statistical analysis to optimize resource allocation, reducing operating costs by 10%, and created reports and interactive dashboards for stakeholders.

Python predictive modeling Statistical Analysis Resource Allocation Data & Analytics Reporting Dashboarding