Hemanth Nagara j

Delivered end-to-end analytical solutions with emphasis on data preparation, feature engineering, and reproducible modeling workflows. Built standardized pipelines covering data ingestion, cleaning, exploratory analysis (EDA), feature construction, and dataset validation to ensure consistency across use cases. Built reusable Python-based workflows to transform raw data into analysis-ready datasets, supporting downstream modeling and reporting. Benchmarked statistical, machine-learning, and deep-learning approaches with consistent evaluation metrics and backtesting strategies. Deployed data solutions for Financial Risk & Exposure Forecasting: time-series pipelines incorporating exogenous variables enabling 30-day forecasting using SARIMAX, XGBoost, and LSTM.

Designed and implemented a serverless data lakehouse architecture using AWS S3 and Athena, migrating legacy Excel workflows to centralized querying. Built Python-based reporting pipelines, improving data quality by 20% and automating KPI delivery via Power BI. Prepared regulatory & audit-compliant reports and automated KPI dashboards in Power BI, reducing manual reporting time by 50%. Cleaned and restructured raw datasets (sales, supply chain, product), improving data quality and ensuring schema consistency and documentation for compliance. Provided peer support and walkthroughs on BI tools, fostering knowledge sharing and adoption across the team.

As an Entrepreneur In Residence, participated in a cohort program to obtain €150,000 in pre-seed funding. Worked with co-founders to conceptualize ideas, research potential customers, gather feedback, develop a minimum viable product, and present pitches to investors. Prototyped NLP & Sentiment Analysis pipelines to extract automated insights from scientific publications for market validation.