Looks like you have JavaScript disabled. For the full Twine experience, you will need to re-enable it.

Data Scientist with 4+ years of experience delivering machine learning, deep learning, and generative AI solutions in financial services and e-commerce. Built predictive and forecasting models that improved accuracy by up to 23% and reduced computing costs by 25%.…

Shanmuka Priyanka R

Data Scientist, AI Engineer, Data Engineer, +2





Data Scientist with 4+ years of experience delivering machine learning, deep learning, and generative AI solutions in financial services and e-commerce. Built predictive and forecasting models that improved accuracy by up to 23% and reduced computing costs by 25%.…

Available to hire

Data Scientist with 4+ years of experience delivering machine learning, deep learning, and generative AI solutions in financial services and e-commerce. Built predictive and forecasting models that improved accuracy by up to 23% and reduced computing costs by 25%.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Language

Work Experience

Data Scientist at The PNC Financial Services Group, Inc.

February 1, 2024 - Present

Developed credit-scoring and financial risk models using XGBoost and logistic regression on 5M+ records, improving default-prediction accuracy by 23% and reducing model drift. Built AI-driven forecasting models (ARIMA, Prophet, LSTM) to improve portfolio risk exposure forecasting by 18% and identify high-risk accounts earlier. Created probability-of-default models supporting $2B+ lending exposure, increasing risk-tier classification accuracy by 15%. Orchestrated end-to-end ML pipelines with Python, MLflow, and CI/CD on AWS SageMaker, reducing deployment cycle time by 40% and standardizing MLOps practices. Ensured compliance with SR 11-7 model risk standards using SHAP explainability and fair-lending checks, producing regulator-ready outputs. Built Tableau and Power BI dashboards to translate model outputs into risk and compliance business intelligence, accelerating decision-making by 30%.

Data Scientist at Web Code IT

September 1, 2020 - August 31, 2022

Engineered and fine-tuned classification and clustering models with scikit-learn to achieve 85%+ accuracy for real-time anomaly detection. Designed e-commerce pricing personalization models (logistic regression, XGBoost, neural networks) to increase customer engagement by 20% and new sign-ups by 15%. Built distributed data pipelines with Spark, Airflow, and Databricks processing 100M+ customer records. Developed a BERT-based NLP pipeline for support-ticket classification, reducing manual triage workload by 30%. Implemented CNN-based computer vision embeddings to improve recommendation accuracy by 12%. Deployed models on AWS SageMaker for real-time APIs serving 1M+ monthly users at 200ms latency. Optimized ML services with Git-based workflows, reducing compute costs by 25%.