Jeremiah Afari Opoku-Acheampong

detroit,michigan

Summary

Data Science and Business Analytics graduate student with experience building AI-powered decision intelligence systems integrating analytics engineering, machine learning, forecasting, simulation, business intelligence, and large language model architectures. Skilled in building end-to-end ELT pipelines, warehouse architectures, operational dashboards, RAG systems, and uncertainty-based decision models using Python, SQL, dbt, BigQuery, Power BI, Streamlit, and LLM frameworks.

Overview

year of professional experience

Work History

AI-Powered Business Reasoning and Decision Support System

- 01.2026

Built an AI-powered Decision Intelligence platform integrating ELT pipelines, forecasting models, RAG workflows, and business-facing dashboards
Designed layered analytics architecture from raw operational data → staging → warehouse → metrics marts using dbt and BigQuery
Developed machine learning pipelines for net sales prediction, high-value order classification, demand forecasting, and shipping delay analysis
Built business dashboards visualizing sales trends, forecast outlooks, KPIs, and operational metrics for business users
Implemented RAG architecture using LangChain and ChromaDB to provide AI-assisted operational recommendations and contextual business reasoning
Created Streamlit interface supporting natural language business queries, AI-generated recommendations, and forecasting visualization
Engineered forecasting datasets using lag features and rolling window techniques
Built query logging and governance tracking system for monitoring AI interactions and decision workflows
Generated operational insights including:
Forecast reliability degradation due to sparse historical monthly observations
High-value order risk patterns affecting operational fulfillment
Revenue trend comparisons between predicted and actual sales performance
Delivered a reusable Decision Intelligence architecture adaptable to healthcare, manufacturing, and enterprise analytics environments
Business Value Delivered:
Automated business insight generation
Reduced analytical dependency on manual SQL reporting
Enabled AI-assisted operational reasoning for non-technical stakeholders
Improved visibility into forecasting reliability and operational risks

Emergency Department Simulation & Decision Analytics System

- 01.2026

Built a healthcare operations simulation modeling emergency department patient flow under uncertain arrival conditions
Simulated staffing, triage operations, ultrasound utilization, emergency care room constraints, and patient wait-time dynamics
Evaluated operational performance using:
Length of Stay (LOS)
Staff utilization
Equipment utilization
Room utilization
Modeled uncertain arrival rates using probabilistic decision trees and performed EMV and EVPI analysis
Built multi-attribute utility models balancing LOS reduction, operational efficiency, and investment cost constraints
Conducted sensitivity analysis across staffing and equipment investment alternatives
Identified PA + Ultrasound expansion strategy as highest utility operational investment under uncertainty
Developed risk profiles and utility-based recommendations for healthcare operational planning
Key Analytical Insights:
Arrival uncertainty significantly affected operational performance and staffing efficiency
Utility-based optimization produced stronger operational decisions than cost-only analysis
Simulation identified bottlenecks in imaging workflows and resource allocation
Decision analysis improved visibility into operational tradeoffs under budget constraints

Analytics Engineering & Warehouse Development

01.2025 - 01.2026

Built enterprise-style analytics engineering workflows using dbt and BigQuery
Developed staging models, warehouse models, feature pipelines, and metrics marts for business analytics
Created fact and dimension tables supporting downstream machine learning and reporting workflows
Performed advanced SQL transformations including joins, aggregations, feature calculations, and business KPI engineering
Built metrics pipelines for inventory analytics, sales reporting, forecasting analysis, and customer reporting
Implemented data quality validation tests and warehouse governance practices
Connected warehouse outputs directly into machine learning and AI reasoning systems
Business Impact:
Improved analytical consistency across operational reporting pipelines
Centralized metrics logic for forecasting and business reporting
Enabled scalable machine learning feature engineering workflows

Deep Learning & Medical Imaging Research

- 01.2025

Developed medical imaging workflows for brain tumor detection and segmentation tasks using deep learning architectures
Applied transfer learning techniques using ResNet models and explored segmentation architectures including U-Net
Investigated generative AI concepts including diffusion models and variational autoencoders (VAEs)
Explored fine-tuning strategies for domain-specific AI applications and medical imaging datasets
Built model training and evaluation pipelines using PyTorch and GPU-enabled workflows

Education

M.S. - Data Science and Business Analytics

Wayne State University

Detroit, MI

01-2026

B.S. - Computer Science

University of Ghana

Legon, Ghana

01-2022

Skills

Programming & Analytics: Python, SQL, Power BI, Advanced Excel, Streamlit, Pandas, NumPy, Scikit-learn, PyTorch
Data Engineering: dbt, BigQuery, ELT Pipelines, Data Warehousing, Data Lakes, Data Marts, Feature Engineering, Dimensional Modeling
AI & MLL: LLMs, RAG, LangChain, ChromaDB, Forecasting, Classification, Fine-Tuning, CNNs, ResNet, U-Net, Diffusion Models, VAEs, Multi-Instance Supervised Contrastive Learning

Decision Analytics: EMV, EVPI, Risk Profiles, Utility Theory, Simulation Modeling, Sensitivity Analysis, Constraint Optimization
Tools: Git, GitHub, Docker, WSL/Linux, AnyLogic, PrecisionTree, OpenAI API

Timeline

Analytics Engineering & Warehouse Development

01.2025 - 01.2026

B.S. - Computer Science

University of Ghana

Deep Learning & Medical Imaging Research

- 01.2025

Emergency Department Simulation & Decision Analytics System

- 01.2026

AI-Powered Business Reasoning and Decision Support System

- 01.2026

M.S. - Data Science and Business Analytics

Wayne State University

BUSINESS & ANALYTICAL CAPABILITIES

Decision Intelligence
Operational Analytics
Forecast Interpretation
Simulation Modeling
Business Process Analysis
KPI Design
Dashboard Development
AI-Assisted Decision Support
Risk & Uncertainty Modeling
Data Storytelling
Scenario Planning
Cross-Functional Analytics