I’m a data scientist and machine learning engineer with a strong foundation in statistics, optimization, and applied AI, focused on building production-ready ML systems and quantitative models.

My work spans end-to-end ML pipelines — data engineering → modeling → evaluation → deployment — with special interest in AI + finance, alternative data, and intelligent decision platforms.

FortuneFlow is an AI-driven personal finance and investment planning platform focused on helping people:

• build healthy financial habits early,
• avoid high-interest debt traps,
• maintain a safety net, and
• make smarter, long-term investment decisions.

Current focus areas

• Personal finance insights + goal-based planning
• Clean UX dashboards and decision flows
• Scalable backend + analytics foundations

➡️ Website: https://fortuneflow.net/

Machine Learning & AI

• Supervised / Unsupervised Learning, Deep Learning (CNNs/Transformers)
• NLP (NER, Relation Extraction, Embeddings), Multi-Task Learning
• Model evaluation, interpretability (SHAP), experiment tracking

Data & Systems

• ETL pipelines, feature stores (concepts), APIs (FastAPI/Django)
• Docker, CI/CD patterns, cloud ML workflows (Vertex AI / AWS / Azure)

Quant & Finance

• Time series modeling, optimization, strategy research & backtesting
• Alternative data signals, risk-aware evaluation

🔹 Gold Trading Strategy
Quantitative research project evaluating multiple gold trading strategies using Google Trends (PyTrends), technical indicators (RSI, MACD, Bollinger Bands, SMA/EMA), and hybrid approaches. Includes signal generation, backtesting, and comparative performance analysis.

🔹 Multi-BioNER (Multi-Task Learning)
A multi-task learning framework for Biomedical Named Entity Recognition (BioNER), leveraging shared representations and cross-task knowledge transfer to improve entity recognition performance across biomedical datasets.

🔹 Recommender System
End-to-end recommender system implementation in Python, focusing on user–item interactions, similarity metrics, and ranking logic. Designed to demonstrate core recommendation algorithms and evaluation strategies.

🔹 Alpha Research
Exploratory quantitative research repository focused on alpha signal discovery, statistical analysis, and experimental trading ideas using market and alternative data.

🔹 Banking GenAI Assistant
A generative AI–powered assistant for banking and financial use cases, showcasing LLM integration, prompt engineering, and practical applications of GenAI in finance.

• LinkedIn: https://www.linkedin.com/in/ronit-gandhi-5a65941aa/
• Portfolio: https://ronitgandhi.com/
• FortuneFlow: https://fortuneflow.net/

⭐ If you find my work useful, feel free to star a repo — it helps!