Senior Product Leader | Generative AI & FinTech Specialist
I architect and scale transformative SaaS and FinTech platforms, with a passion for leveraging AI to drive financial inclusion in emerging markets. My focus is on building data-driven, user-centric products that solve real-world problems for underbanked populations.
- Product Leadership: Vision, strategy, and end-to-end lifecycle management for super apps and AI-powered platforms.
- Generative AI & ML: Designing and implementing solutions using LLMs (GPT, BERT), RAG, LangChain, and predictive models.
- Research & Data Analysis: Conducting market research, trend analysis, and data-driven experimentation to uncover insights and guide strategic decisions.
- Platform Innovation: Building scalable, offline-capable systems for low-connectivity environments.
- Cross-Functional Leadership: Mentoring high-performing teams of engineers and data scientists to deliver complex, impactful products.
| Category | Technologies & Skills |
|---|---|
| Product Management | A/B Testing, Roadmapping, PRD Writing, Agile/Scrum, GTM Strategy, OKRs, Customer Discovery |
| Generative AI | LLMs (GPT, BERT, T5) RAG Architecture LangChain LlamaIndex Prompt Engineering Fine-tuning Vector Databases AI Agents Multi-modal AI |
| Machine Learning | Supervised Learning Unsupervised Learning Reinforcement Learning Ensemble Methods Transfer Learning |
| ML Algorithms | Linear/Logistic Regression Decision Trees Random Forest SVM XGBoost K-Means DBSCAN PCA K-NN Naive Bayes ARIMA LSTM GRU |
| Deep Learning | Neural Networks CNN RNN Transformers Autoencoders GANs Transfer Learning Attention Mechanisms |
| ML Frameworks | TensorFlow PyTorch Keras Scikit-learn Hugging Face XGBoost LightGBM CatBoost |
| NLP & Text Analytics | Sentiment Analysis Text Classification Named Entity Recognition Topic Modeling Text Generation Text Summarization Machine Translation Language Modeling |
| Computer Vision | Image Classification Object Detection Image Segmentation Image Generation OCR |
| MLOps & Deployment | AWS SageMaker Google Cloud ML Azure ML Docker Kubernetes Flask FastAPI MLflow Kubeflow Model Registry Feature Store |
| Data Engineering | Apache Spark PySpark Apache Kafka Hadoop Airflow Data Pipelines ETL/ELT Real-time Analytics Data Warehousing |
| Programming & Data | Python R SQL JavaScript Pandas NumPy SciPy Matplotlib Seaborn Plotly |
| Research & Data Analysis | Market Research Trend Analysis Statistical Analysis Hypothesis Testing Experimental Design Customer Insights Competitive Analysis Causal Inference |
| Data Visualization | Tableau Power BI Looker Dashboard Design Data Storytelling Business Intelligence |
| Cloud Platforms | AWS Google Cloud Microsoft Azure SAP BTP |
Generative AI Expertise:
- Large Language Models (LLMs): Fine-tuning, prompt engineering, RAG systems
- AI Agent development with LangChain and LlamaIndex
- Multi-modal AI systems (text-to-image, text-to-video)
- Offline-capable AI solutions for low-connectivity regions
Machine Learning Specializations:
- Predictive Modeling: Time series forecasting, classification, regression
- Natural Language Processing: Sentiment analysis, text classification, NER
- Computer Vision: Image analysis, object detection, generative models
- Recommendation Systems: Collaborative filtering, content-based filtering
- Anomaly Detection: Fraud detection, system monitoring
ML Operations & Engineering:
- End-to-end ML pipeline development
- Model deployment and serving at scale
- Performance monitoring and model drift detection
- Feature engineering and management
- Automated ML (AutoML) workflows
- Scaled a Super App from 0 to 10,000 MAUs, achieving 300% YoY user growth through data-driven market analysis.
- Architected an AI-driven dynamic pricing engine that increased platform revenue by 25% using ensemble methods and time series forecasting.
- Pioneered proprietary Generative AI models for hyperrealistic image and video generation, reducing content production costs by 60%.
- Developed offline-capable LLM applications using RAG architecture, enabling AI functionality in rural, low-connectivity regions.
- Built ML-based supply chain forecasting models (Random Forest, LSTM) that saved clients $500k annually.
- Created predictive agriculture models using Scikit-learn that improved crop yields by 20% for 1,000+ farmers.
- Implemented real-time NLP systems for sentiment analysis and text classification, enhancing UX for low-literacy users.
- Vibe Coding: Rewel AI Labs
- LinkedIn: Rewel Mumbo
- Advanced RAG Systems for enterprise knowledge management
- Multi-modal AI applications for emerging markets
- Edge AI deployment for low-connectivity environments
- AI-powered financial inclusion platforms
Bridging the gap between cutting-edge AI research and practical, scalable solutions that empower underserved communities through technology.# Rewel