DICKSON OKORIE

Collaborated with key stakeholders to gather and refine requirements for the design and implementation of an end-to-end data analytics platform.

Designed and deployed a Microsoft Fabric Environment, building scalable ETL pipelines using PySpark and implementing GIT version control via Azure DevOps.

Developed and maintained 10+ interactive Power BI dashboards with KPI tracking models, to deliver real-time insights to diverse stakeholder groups.

Managed Microsoft Azure database and utilized SQL & Python to extract, transform, and analyze large datasets for decision-making.

Designed predictive models using regression analysis and time series forecasting to optimize resource allocation and reduce patient wait times by 20%.

Applied hypothesis testing and A/B testing to validate assumptions on discharge trends, improving patient flow and operational efficiency.

Developed cost-saving models that identified clinical procurement inefficiencies, resulting in a £3M vendor cost reduction.

Implemented data privacy and security protocols, ensuring compliance with GDPR and DPA, to safeguard sensitive information and reduce data breach risks.

Drove the requirement-gathering processes for both projects by engaging directly with relevant stakeholders to define project scope, objectives, and performance metrics.

Ensured the highest level of data quality by overseeing the cleaning, processing, and merging of large datasets from respective databases (Microsoft SQL Server and Google BigQuery) using advanced SQL queries.

Implemented Natural Language Processing (NLP) techniques using Python (SpaCy, TextBlob) to perform sentiment analytics on customer feedback and social media data for the media organization.

Conducted in-depth data analysis to identify trends and patterns within relevant datasets and utilized Power BI to build interactive dashboards, leveraging Power Query and DAX.

Implemented Power BI-based KPI tracking which Identified opportunities within the NHS that reduced vendor spend by 12%.

Provided data-driven insights that guided content strategies, achieving a 35% improvement in customer engagement for the Media Organization.

Spearheaded data analysis projects aimed at monitoring key performance indicators (KPIs), improving underwriting profitability and managing loss ratios across various lines of business.

Developed and deployed a logistic regression model to identify high loss-making transactions and simulate profit-making approaches, reducing the loss ratio from 123% to 46%.

Led the development and implementation of an end-to-end insurance claims portal which enhanced customer experience, reduced complaints on claims by 35%, and improved net promoter score (NPS) by 120%.

Oversaw the production and timely delivery of periodic reports and analyses that directly supported strategic decision-making, using Microsoft SQL Server (SSMS, SSIS, SSAS & SSRS).

Championed the development of a fraud detection model by implementing machine learning anti-fraud frameworks and business rules, which resulted in 15% fraud savings.

Conducted financial analysis of expenses in Microsoft Excel using advanced functionalitiessuch as VLOOKUP, pivot tables, and power queries for detailed cost breakdowns.

Evaluated and processed claims across several lines of business including motor insurance and property & casualty.

Coordinated with loss adjusters to conduct complex claim investigations and managed recovery through subrogation, salvage, and reinsurance.

Generated data-driven insights on loss ratios, reinsurance trends, and claim run-offs, supporting strategic pricing decisions and boosting underwriting profitability.