Claims Processing & Help Desk Professional (Remote)

RONALD DDIBYA

Iowa City, IA ******.******@*****.*** 319-***-**** LinkedIn GitHub

PROFESSIONAL SUMMARY

Strategic analyst & finance professional with dual M.S. degrees in Business Analytics and Finance from the University of Iowa, combining advanced analytics, econometrics, and financial modeling with hands-on machine learning expertise. Experienced in price and promotion optimization, demand forecasting, customer segmentation, and A/B testing to drive measurable business performance. Skilled in translating complex statistical analyses into actionable strategies for senior leadership, supporting data- driven decision-making in fast-paced, cross-functional environments. Brings a unique perspective from both corporate analytics and frontline operations, ensuring solutions are both technically rigorous and commercially practical. EDUCATION

MS., Business Analytics MS., Finance GPA: 3.49 May 2024 University of Iowa, Tippie College of Business Iowa City, IA MS., Environment & Natural Resources GPA: 3.49 Jan 2018 Makerere University Kampala, UG

BS., Industrial Chemistry GPA: 3.03 Jan 2013

Makerere University Kampala, UG

KEY SKILLS

• Analytics & Modeling: Price Optimization, Demand Forecasting, Segmentation, Time Series, A/B Testing, Test-and-Learn Methodologies.

• Machine Learning: Regression, Classification, Ensemble Methods, Gradient Boosting, Random Forest, SVM, Neural Networks, Deep Reinforcement Learning.

• Data Mining & Engineering: Data cleaning, preprocessing, ETL pipelines, feature engineering, clustering, classification, association rule mining, anomaly detection, text mining, and pattern recognition.

• Technical Tools: Python, SQL, SAS, Excel, VBA, GitHub, Orange Software, JMP Pro, scikit-learn, TensorFlow, Pandas, NumPy, Alteryx, IBM SPSS, Microsoft Suite, Bloomberg Terminal, SAP, HTML, @Risk, vlookups, pivot tables, Goalseeker.

• Visualization: Tableau, Power BI, matplotlib, seaborn, Excel visuals

• Soft Skills: Communication, Time Management, Cross-Functional Collaboration, problem structuring.

• Financial skills: Financial Modeling & Valuation, Financial Analysis, Portfolio Analysis, M&A, Corporate Financial Reporting, Sustainable Finance, Derivatives, Trading, Wealth Management, Life & Health Insurance, Fixed Income Analysis, Market Research, Project Management, Financial Planning & Analysis. PROFESSIONAL EXPERIENCE

Data Scientist / AI Solutions Developer (GitHub) Mar 2025 – Present Independent Project Iowa City, IA

• Designed and deployed the LMIC Health Insights Toolkit, an end-to-end AI prototype for malaria-like symptom triage in LMIC contexts, integrating predictive modeling (AUC: 0.6828), drift monitoring (MSE: 0.0062), fairness evaluation, agent-based insights, and a lightweight chatbot.

• Built synthetic datasets to protect privacy while enabling open collaboration and reproducibility.

• Conducted subgroup fairness analysis by sex and region, identifying disparities for pre-deployment mitigation.

• Developed A/B testing simulations to evaluate outreach strategies for health interventions.

• Created a learning script and documentation to enable replication and adaptation by local partners. Data Scientist / Engineer (GitHub) Sep 2025 – Present Capstone Project: End-to-End Azure Data Pipeline for Real-Time Sales Analytics Iowa City, IA

• Designed and orchestrated ETL/ELT data pipelines using Azure Data Factory for data ingestion and transformation.

• Built scalable big data processing workflows using PySpark on Azure Databricks and integrated Delta Lake for data versioning and reliability.

• Managed data storage solutions across Azure Blob Storage, Data Lake Gen2, Azure SQL Database, and Cosmos DB.

• Developed real-time analytics pipelines leveraging Azure Event Hubs and Stream Analytics.

• Strengthened proficiency in data modeling, orchestration, and optimization for cloud-native environments. Fixed Income Analyst Jan 2024 – May 2024

Hart Fund, University of Iowa Iowa City, IA

• Conducted comprehensive analysis of fixed income securities using Bloomberg Terminal and Excel, focusing on yield spreads, duration, convexity, credit ratings, and liquidity risk to assess portfolio performance.

• Built & maintained bond valuation & yield curve forecasting models in Excel integrated with Bloomberg data feeds, enabling data-driven investment decisions that outperformed the benchmark by 0.9%.

• Applied portfolio optimization techniques in Excel (mean-variance & duration-matching models) to rebalance holdings, reducing portfolio volatility by 4.5% while maintaining desired return targets.

• Performed sensitivity, scenario, & stress testing analyses to evaluate interest rate and credit risk exposure across multiple fixed income instruments, improving risk-adjusted return by 6%.

• Collaborated with fund managers & analysts to align quantitative insights with broader strategic goals, strengthening decision-making & deepening expertise in Bloomberg functions (YAS, DES, WEI, SRCH, PORT) for portfolio analysis as well as performance attribution.

Graduate Assistant – Economics Jan 2023 – May 2024 University of Iowa Iowa City, IA

• Led classroom discussions that enhanced student engagement and comprehension by 30%.

• Offered personalized academic support during office hours, contributing to an 80% increase in student performance.

• Developed and implemented innovative teaching strategies to address diverse learning needs. Financial Analyst – International Business & Finance Consulting in Africa May 2023 - Dec 2023 Institute for International Business, University of Iowa Iowa City, IA

• Contracted through the Institute to establish data and financial infrastructure for three start-up companies in Africa, supporting their integration into U.S.-based reporting and compliance systems.

• Developed & implemented database systems using MS Access, SQL, & VBA to manage operational, financial, & compliance data, significantly improving data accuracy & accessibility.

• Designed automated financial statement reporting systems using MS Access, SQL, & VBA, aligned with U.S. regulatory standards, reducing reporting cycles by 30%, enhancing the start-ups’ transparency & audit readiness.

• Conducted detailed financial analyses in Excel, including profitability, liquidity, & cash flow metrics, enabling each start- up to identify inefficiencies, optimize cost structures, and improve capital utilization by up to 18%.

• Collaborated with cross-border teams to align business analytics with strategic objectives, driving more data-informed decision-making as well as long-term financial sustainability. Lead Consultant – ESG & Sustainability Aug 2015 – July 2022 Ecoserv Limited Kampala, UG

• Built implementable performance tracking frameworks for development projects in energy, infrastructure, waste management, manufacturing, oil & Gas, mining industry, improving compliance efficiency by 25%.

• Developed financially optimized environmental strategies, balancing sustainability goals with budget constraints.

• Proposed cost-effective & feasible mitigation measures while undertaking ESIAs for development projects, reducing environmental compliance costs for key stakeholders by up to 30%. SELECTED PROJECTS (refer to my repository; GitHub for more detailed projects description) Bank Marketing Campaign Prediction: Analyzed customer response data from a bank’s marketing campaign. Built and compared predictive models (XGBoost, Random Forest, Logistic Regression, Neural Network) to forecast campaign success. Achieved an AUC of 0.795 and used Excel to determine profit curve analysis to recommend targeting strategies that improved ROI. Financial Modeling & Valuation – Foot Locker Inc: Led a valuation analysis of Foot Locker Inc. by building integrated financial statements and forecasting future performance. Created DCF and LBO models, ran peer comparisons and sensitivity tests, and synthesized findings into a concise investment memo for the team. Soccer Match Outcome Prediction: Created interactive machine learning models (Random Forest, Logistic Regression, SVM, KNN) with Python scripting and ipywidgets, achieving 63% predictive accuracy; automated model evaluation workflows and visualization scripts for real-time updates.

CERTIFICATION AND TECHNICAL TRAINING

Professional Certificate in Large Language Model Operations (LLMOps) by edx & Pragmatic AI Labs – On-going: Courses: Introduction to Generative AI, Large Language Models with Azure, Generative AI and LLMs on AWS, Data Engineering with Databricks, Open Source LLMOps, Advanced Data Engineering, Applied Local Large Language Models. Azure Data Engineering: Comprehensive hands-on training focused on designing, building, and managing modern data pipelines in the Microsoft Azure ecosystem. Skills gained: SQL, Python, PySpark, Azure Data Factory (ADF), Azure Databricks, Delta Lake, Synapse Analytics, Azure Blog Storage, Data Lake Gen2, SQL DB, Cosmos DB.

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