Vaibhav Uppal

Data Scientist (Working Student)

• Job Details:Analyzed capital investment finance data sources (PostgreSQL) to develop ML demand forecasting time series models using Python. Automated Power BI & Excel reporting, reducing manual effort by 40%. Used XAI models (LIME, SHAP) to enhance model transparency for stakeholders.

Thesis: Cloud Classification through NN

• Job Details:Performed predictive analytics using neural networks (CNN-BiLSTM) to evaluate streaming video feeds & photovoltaic features. Forecasted cloud types achieved a final accuracy of 78%.

Risk Data Analyst (Working Student)

• Job Details:Performed data validation through regression analysis to uphold data quality. Built ETL pipeline with big data tools (Spark, Hadoop) to optimize data workflows. Devised and deployed Python-based credit risk models (scikit-learn, Keras), amplifying detection accuracy by 60%. Constructed Power BI dashboards to visualize KPIs (like risk scores) & applied NLP (NLTK) for feedback analysis, refining loan approvals.