Data Scientist with hands-on experience in Machine Learning, Deep Learning, and Generative AI (LLMs/RLHF), working across the full lifecycle: ETL/ELT, predictive modeling, deployment, MLOps, and monitoring. Background in real-time fraud detection (30K+ transactions/day), LLM refinement with RLHF, and analytical solutions on GCP.
Currently pursuing a Postgraduate in AI & Health Data Science at Instituto Sírio-Libanês and an MBA in Data Science & AI at USP/Esalq.
- Based in Curitiba, PR, Brazil
- 454+ public repositories across 10+ languages
- Certified by Google, IBM, Johns Hopkins & Wharton
- Open to opportunities in Data Science, MLOps & GenAI
Ensemble of 4 models (RF, XGBoost, Neural Networks, Autoencoders) with end-to-end MLOps pipeline. AUC 0.94 | Latency < 200ms | 30K+ transactions/day.
| Real-time analytics processing 10K+ events/second for market microstructure insights, trading signal generation, and performance monitoring.
|
Medical entity extraction (ICD-10, medications, symptoms) from clinical texts using BERTimbau/BioBERTpt Transformers with optimized NER F1-score.
| End-to-end pipeline for DNA-seq, RNA-seq, single-cell & ChIP-seq workflows with ML-based insights on HPC and cloud (AWS, GCP, Azure).
|
Fairness auditing for HR models: 5 metrics (Disparate Impact, Demographic Parity, Equal Opportunity), SHAP by group, 3 mitigation techniques, automated HTML reports. 62 tests.
| Organizational Network Analysis with NetworkX: centrality metrics, bottleneck detection, knowledge loss risk, Louvain community detection, executive recommendations. 68 tests.
|
End-to-end MLOps pipeline for predicting employee turnover risk with automated retraining, model monitoring, and drift detection.
| RAG-powered assistant for HR policy Q&A using LLMs with retrieval-augmented generation over corporate policy documents.
|
450+ repositories spanning Data Science, ML/AI, Data Engineering, Quantitative Finance, HealthTech, HR Tech, and more. Explore all repositories →
 Advanced Data Analytics Data Analytics |  AI Engineering Data Engineering Machine Learning GenAI Engineering Deep Learning Data Science |  Data Science Specialization |  Business Analytics UPenn |
| Degree | Institution | Period |
|---|---|---|
| Postgraduate — AI & Health Data Science | Instituto Sírio-Libanês (IEP/HSL) | 2026 – 2027 |
| MBA — Data Science, AI & Analytics | USP / Esalq | 2026 – 2027 |
| B.Tech — Systems Analysis & Development | UniDomBosco | 2022 – 2025 |
| B.Tech — Cyber Defense | UniDomBosco | 2022 – 2025 |
| B.Tech — IT Management | UniDomBosco | 2022 – 2025 |
| Data Scientist (Professional) | EBAC | 2024 – 2025 |
Analista de Dados / Cientista de Dados — trade2go (Out/2025 – Mar/2026)
├── Full ML/AI cycle (POC → Production): regression, classification, clustering
├── EDA on 2M+ records datasets, identifying business KPI patterns
└── 6+ dashboards (Power BI, Looker Studio) | SQL optimization (+40% performance)
Data Science Researcher — Manus AI (Mar/2025 – Present)
├── R&D in AI / ML / Deep Learning: 5+ architectures benchmarked
└── Feature engineering on 80+ raw features (+8% accuracy improvement)
Analista de Cibersegurança — Sicredi PJ/Contt (Jan/2023 – Jun/2025)
├── Real-time fraud detection: RF, XGBoost, Neural Nets, Autoencoders (-28% FP)
├── MLOps pipeline: Python, TensorFlow, Kafka, Spark, MLflow (99.2% uptime)
└── Anomaly detection contributing to -15% in financial losses
Estagiário Dev Fullstack — EBANX (Mar/2022 – Jan/2023)
├── Scalable web applications (PHP, JS, HTML5, CSS)
└── MySQL query optimization (-25% response time)
mindmap
root((Gabriel Lafis))
Machine Learning
Supervised & Unsupervised
Ensemble Methods
Hyperparameter Optimization
Feature Engineering
Deep Learning & NLP
Transformers & BERT
LLMs & RLHF
NER & Text Mining
Computer Vision
MLOps & Engineering
CI/CD Pipelines
Model Monitoring
Docker & Kubernetes
Real-Time Streaming
Data Engineering
ETL/ELT Pipelines
Apache Spark & Kafka
Data Warehousing
BigQuery & GCP
Domain Applications
Financial Fraud Detection
HealthTech & Clinical NLP
Quantitative Finance
HR Tech & People Analytics
