Nguyen Dai Hoang - Curriculum Vitae

Professional Summary

Dedicated and research-oriented Data Engineering Intern at SSI Securities Corporation with strong foundation in Quantitative Finance, Big Data pipelines, and Applied Machine Learning. Proven track record in architecting financial analytics platforms visualizing 15 quarters of corporate financial statements across 1,524 stock symbols, developing statistical valuation terminals (±1SD/±2SD bands, Graham multiplier, Box Plot IQR) for Vietnam equity markets, implementing biologically plausible deep learning architectures (Hinton’s Forward-Forward algorithm), and engineering hybrid time-series forecasting models (ARIMA + Bi-LSTM). Holder of prestigious credentials including Google Data Analytics Professional Certificate, Google AI Professional Certificate, and CPMAI.

Education

Thai Nguyen University of Information and Communication Technology (ICTU) 2023 — 2027 (Expected)

Bachelor of Science in Information Technology — International Institute of Training (IIT) Thai Nguyen, Vietnam

Key Coursework: Data Structures & Algorithms, Database Systems Design, Machine Learning, Deep Learning, Distributed Systems, Software Engineering, Advanced Applied Mathematics.
Academic Focus: Financial Data Engineering, Deep Learning for Time-Series Analysis, High-Throughput Analytics Infrastructure.

Professional Experience & Internship Projects

SSI Securities Corporation Hanoi / Remote, Vietnam | 2026 — Present

Data Engineering Intern — Data & Fintech Solutions Division Verified Internship

SSI Analytics Engine (Enterprise Financial Analytics Platform) [Live Platform ↗]: Architected and deployed a multi-quarter financial analytics engine processing 15 consecutive quarters of financial statements (2022–2025) across 1,524 listed companies on HOSE, HNX, and UPCOM. Automated the computation of core fundamental metrics (Revenue, NPAT, EPS, ROE, P/E ratio, Yield Trends), reducing investment research turnaround time by 75%.
Market & Stock Valuation Terminal [Live Terminal ↗]: Engineered a comprehensive financial valuation terminal for the Vietnamese equity market. Implemented 5-year statistical valuation bands (±1SD, ±2SD, Mean, Percentile) and Box Plot (IQR) quartiles (Min, Q1, Median, Q3, Max) for market indices (VNINDEX, VN30, HNX) based on P/E, P/B, and Benjamin Graham's Composite Valuation (P/E × P/B).
Integrated single-stock 20-quarter valuation tracking with dynamic percentile positioning, alongside an instant multi-criteria screener evaluating 1,522+ listed tickers with real-time URL routing and automated CSV report generation.
GoldenStock (Real-Time Market Analytics Dashboard) [Live System ↗]: Engineered a responsive financial analytics dashboard integrating TradingView interactive candlestick charting, live price feeds, and custom watchlist persistence using Next.js, TypeScript, and React Query.

Scientific Research & Machine Learning Projects

Forward-Forward Algorithm Implementation (FF-MNIST) 2026

Academic Research | Supervisor: Dr. Nguyen The Vinh Kaggle Code & Report ↗

Implemented Geoffrey Hinton’s 2022 Forward-Forward (FF) Algorithm in PyTorch as a biologically plausible, gradient-free alternative to classical Backpropagation.
Evaluated dual forward passes (positive vs. negative data) with layer-independent local goodness threshold updates, eliminating backpropagation memory overhead and validating potential for low-power neuromorphic hardware execution.
Technologies: PyTorch, Python, NumPy, Deep Learning, Scientific Computing.

Hybrid ARIMA + Multi-Feature Bi-LSTM for Stock Price Forecasting 2026

Applied Quantitative Research | Supervisor: Dr. Tran Quang Quy Kaggle Notebook ↗

Engineered a two-stage hybrid forecasting architecture for FPT stock price series by combining econometric time-series modeling with deep sequential learning.
Utilized ARIMA to model linear market trends and seasonality, feeding non-linear residual sequences into a Multi-Feature Bidirectional LSTM network, achieving superior predictive precision (reduced RMSE & MAPE) over standalone models.
Technologies: TensorFlow, Keras, statsmodels (ARIMA), Bi-LSTM, Scikit-learn, Quantitative Finance.

Proactive Customer Churn Prediction System (SSI Securities) 2026

Enterprise Machine Learning | Supervisor: Dr. Nguyen The Vinh Production Architecture

Designed an early-warning machine learning pipeline to identify brokerage accounts at risk of churning within a 90-day window.
Handled severe dataset class imbalance using SMOTE, trained a hyperparameter-tuned XGBoost model, and integrated SHAP (SHapley Additive exPlanations) to deliver interpretable churn driver insights directly to Microsoft Dynamics 365 CRM workflows.
Technologies: Python, XGBoost, SMOTE, SHAP, Scikit-learn, CRM Integration, Fintech.

Professional Certifications & Licenses

Google Data Analytics Professional Certificate — Google | Coursera (Specialization: EGQUSP5Z6VW4)

• Rigorous 8-course credential covering full data analysis lifecycle: SQL data extraction, data cleaning, Tableau visualization, and Python/R analysis for data-driven decisions.

2026 | Verify Credential ↗

Google AI Professional Certificate — Google | Coursera (Specialization: GJECLFWDGC9U)

• 7-course professional specialization: Fluency in GenAI workflows, prompt engineering patterns, Google Gemini, and responsible AI system deployment.

2026 | Verify Credential ↗

Cognitive Project Management for AI (CPMAI) — Cognilytica

• Industry-standard methodology for enterprise AI/ML project lifecycle governance, scoping, data preparation, evaluation, and operationalization based on extended CRISP-DM.

2026 | View Certificate ↗

Technical Skills & Competencies

Programming & Query: Python (Pandas, NumPy, statsmodels, SciPy), SQL (PostgreSQL, MySQL, Complex CTEs, Window Functions, Optimization), TypeScript, JavaScript, PHP, R (Basics).

Data Engineering & Cloud: Apache Spark (PySpark), Apache Airflow (DAGs, ETL/ELT Scheduling), dbt Core, Data Warehousing (Kimball Dimensional Modeling), Docker, Linux/Bash, Git / GitHub Actions CI/CD.

Machine Learning & AI: PyTorch, TensorFlow / Keras, Scikit-learn, XGBoost, Bi-LSTM, ARIMA, SHAP Interpretability, SMOTE, Generative AI & Prompt Engineering.

Analytics, Viz & Web: ApexCharts, Tableau, TradingView Charts, Financial Valuation Models (P/E, P/B, Graham P/E × P/B, ROE), Next.js, Tailwind CSS, RESTful APIs.