AI Engineer, Data Scientist & Fintech Technologist

I design intelligent systems that automate decisions, blending purposeful code with sharp analysis at the intersection of Finance and AI.

Hi, I'm Lenin. Nice to meet you.

With a foundation in finance and over 5 years of experience in investment banking, I transitioned into the world of data science and AI to solve complex, real-world problems. I've since built intelligent systems for stock pattern recognition, autonomous agents, and AI-powered tools across finance and business. I'm deeply curious, always experimenting, and passionate about blending smart code with meaningful impact.

My Expertise

Machine Learning

Supervised & Unsupervised Learning
Decision Trees, Random Forest, Gradient Boosting
Regression & Classification
Clustering (K-Means, DBSCAN)
Feature Engineering & Data Preprocessing
Model Evaluation & Cross-Validation
Time Series Forecasting
Scikit-learn, XGBoost, LightGBM

Deep Learning

ANNs, CNNs, RNNs
LSTM for sequence modeling
Transformers for NLP
Transfer Learning & Fine-tuning
Image Classification & NLP
Text Generation
TensorFlow, Keras

Generative AI

LangChain, Hugging Face, OpenAI APIs
ChatGPT-like Agents & RAG systems
Prompt Engineering
Vector Databases (FAISS)
Crew AI & AgentOps
Quantization, LoRA
Mistral Models
Streamlit Apps, AWS EC2 Deployment

Self-Built AI Startup Projects

Built independently to solve real-world problems using Generative AI, NLP, and automation.

ChatGPT-like AI Chatbot with Web Search

Built a domain-adaptable chatbot using LangChain, OpenAI, FAISS, and Google Custom Search API. It retrieves context-aware answers via vector similarity, enriches responses with live web results, and handles small talk intelligently. Features include real-time knowledge updates, RAG-based architecture, and Streamlit UI deployed on AWS EC2.

Try the Chatbot

Stock Market Signal Engine with AI & Indicators

Created an LLM-based chatbot that analyzes stock trends using RSI, MACD, SuperTrend, OBV, sentiment from Reddit, and ML models. Users can chat via a Streamlit UI, receiving context-aware insights. Powered by LangChain agents, vector search (FAISS), and deployed on AWS.

Analyze with AI