Machine Learning • NLP • RAG • LLM Evaluation

Data Scientist building reliable ML and applied AI systems

Building and evaluating predictive ML, NLP, and RAG applications with Python, scikit-learn, PyTorch, Transformers, FastAPI, retrieval evaluation, and cloud deployment.

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Featured Data Science • ML • Applied AI

Financial Complaint Auto-Routing NLP workflow showing leakage-safe preparation, TF-IDF and DistilBERT evaluation, selective routing, and retrospective validation.

ML / NLP / MODEL EVALUATION

COMPLETED V1–V2 STUDY

Financial Complaint Auto-Routing with NLP

Leakage-safe machine learning and NLP study for eight-class CFPB complaint classification, comparing a locked TF-IDF + Linear SVM benchmark with a frozen DistilBERT challenger and human-in-the-loop routing.

Identified and remediated 39.39% normalized-text leakage in the original test split; corrected group-aware development/final-test splits achieved zero normalized-text overlap.
On the shared 2024 benchmark, the frozen DistilBERT challenger increased Macro F1 from 0.7671 to 0.7949; both frozen models were later compared on a 30,156-row retrospective 2025 cohort.

Pythonscikit-learnTF-IDFLinear SVMPyTorchDistilBERTModel Evaluation

GitHub Repo Case Study Architecture

CivicLens hybrid RAG workflow showing NYC 311 document ingestion, pgvector retrieval, cited answers, Next.js UI, analytics routing, and local evaluation.

APPLIED AI / RAG / RETRIEVAL EVALUATION

HOSTED PORTFOLIO DEMO

CivicLens RAG — NYC 311 Operations Copilot

Hosted portfolio RAG application for grounded NYC 311 documentation Q&A with semantic + full-text retrieval, validated citations, explicit abstention handling, and bounded analytics.

Combined semantic search and PostgreSQL full-text retrieval with deterministic Reciprocal Rank Fusion (RRF) over curated NYC 311 knowledge.
In the approved real-local evaluation, hybrid retrieval reached 83.9% Recall@5 and 92.9% expected-source retrieval across 14 retrieval-eligible questions.

PythonHybrid RetrievalRRFPostgreSQLpgvectorFastAPIRetrieval Evaluation

Live Demo Case Study GitHub Repo Architecture

Data & Cloud Foundations

AZURE DATA ENGINEERING

NYC 311 Service Requests Lakehouse

Azure-first medallion lakehouse for NYC 311 operational analytics, transforming raw API data into analytics-ready bronze, silver, and gold datasets.

Azure Data FactoryADLS Gen2DatabricksPySparkDelta LakePythonSQLPower BIGitHub Actions

Case Study GitHub Repo Architecture Proof

REAL AWS CLOUD PROOF

Cloud Flight Fare Pipeline

Real AWS cloud proof project showing EventBridge Scheduler -> ECS/Fargate -> Flight API -> S3 Bronze -> Redshift Serverless -> dbt staging/marts/tests -> CloudWatch Logs, with proof screenshots, runbooks, and cost/secret safety notes.

AWSECS/FargateEventBridgeS3RedshiftdbtDockerCloudWatch

Case Study GitHub Repo Architecture Proof

PYTHON DATA INGESTION

Travelpayouts Flight Collector

Python API ingestion project that collects live Travelpayouts flight fare data and publishes dated CSV snapshots for analytics.

PythonAPI IngestionCSVSchedulingpytestGitHub Actions

GitHub Repo Data

Supporting Analytics & Applications

DATA SCIENCE

Flight Price Analytics

Time-based Buy/Wait classification and fare forecasting using route-level price snapshots, feature engineering, and backtesting.

Pythonscikit-learnForecastingTime-Based SplitPower BI

GitHub Repo ML Pipeline

DATA ANALYTICS

Floral Daily SKU Analysis

Daily SKU sales, margin, promotion, holiday, and waste analysis using Python, SQL, and Power BI to support inventory and business decisions.

PythonSQLPower BIInventory AnalyticsTrend Analysis

GitHub Repo SQL Analysis

AI REPORTING SAAS

Sumryze - AI-Powered SEO Reporting Dashboard

SaaS-style dashboard for automated SEO reporting, AI-generated summaries, analytics visualizations, and client-ready insights.

Next.jsTypeScriptTailwindOpenAIREST APIsVercel

GitHub Repo Live Site

Skills & Tools

Programming & Analysis

PythonSQLpandasNumPyStatistical Analysis

Data Science & Machine Learning

scikit-learnPyTorchTransformersNLPPredictive ModelingText Classification

Model & LLM Evaluation

Macro F1Model ComparisonLeakage-Safe ValidationTemporal ValidationRetrieval EvaluationError / Failure Analysis

Applied AI & RAG

EmbeddingsVector SearchHybrid RetrievalPostgreSQL/pgvectorRRFGrounded GenerationCitation ValidationSafe Abstention

Data & Cloud Engineering

AWSAzureDatabricksPySparkdbtDelta LakeData Pipelines

Software & Production

FastAPIDockerGitHub ActionsAPIsTestingCI/CD

About

I’m a Data Scientist focused on applied AI, machine learning, and NLP. I build and evaluate production-oriented ML and generative AI applications spanning predictive modeling, retrieval, RAG, and LLM evaluation, with particular attention to data quality, failure modes, grounded outputs, and reliable evaluation.

I’m currently completing an M.S. in Information Technology with a Data Analytics concentration at Middle Georgia State University, expected December 2026. My graduate coursework emphasizes data science, machine learning, predictive analytics, and statistical modeling.

My software development foundation and cloud data engineering experience across AWS and Azure help me connect the full workflow—from data ingestion and transformation to models, APIs, deployment, and user-facing applications.

Contact

Interested in collaborating on data science, applied AI, or portfolio projects? Reach out and I will follow up.

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