

Data Scientist & Risk Analyst with 6+ years in credit risk, fraud analytics, predictive modeling, and AI/ML. Skilled in Python, SQL, Databricks, scorecards, segmentation, and ML deployment.
Programming & Tools: Python, SQL, C, C, Matlab, Java, R, Shell Scripting
ML & AI: Predictive modeling, Scorecards, Decision Trees, Random Forests, Gradient Boosting, Ensembles, TensorFlow, PyTorch, Scikit-learn, Keras
Risk & Analytics: Credit risk modeling, Bureau analytics, Fraud detection, Scorecards (M/B), Risk Tiers (RT1–RT5), Vintage analysis, Exclusion waterfall, Multipliers
NLP & CV: BERT, NLTK, Gensim, Dialogflow, OpenCV, FaceNet, MTCNN
Visualization & Tools: Pandas, NumPy, Databricks, Tableau, Power BI, Plotly, Matplotlib, Seaborn
Cloud & Platforms: Azure, Google Colab, Databricks; Keywords: Model governance, Portfolio monitoring, Regulatory compliance, Underwriting