Jaishil Trivedi
About Candidate
Data professional with hands-on experience across the full data lifecycle – processing, analysis, quality assurance, and insights reporting – gained through applied work on credit risk, classification, and business performance analytics. Built and deployed an AI-powered Diagnostic Report Generator using the Anthropic Claude API that cut client report turnaround from hours to seconds. Proficient in Python, SQL, and Tableau, with practical exposure to Generative AI (GenAI) applications in data analysis. Comfortable extracting data from relational databases, engineering features for risk and classification models, and translating complex data insights into clear takeaways for non-technical, cross-functional stakeholders.
Location
Education
Bachelor's of engineering degree in information technology department feom gandhinagar institute of technology (gtu).
Pg program in data science and Ai engineering course and internship
Work & Experience
Contributed to live ML projects (classification, regression, credit risk) – built POC models used as analytical inputs for
production systems across multiple client engagements, appropriately assessing data quality and risk at each stage.
Applied end-to-end data science workflow: cleaning, feature engineering, model selection (XGBoost, LightGBM,
Scikit-learn), hyperparameter tuning (GridSearchCV / RandomizedSearchCV), and evaluation.
Designed and delivered an AI-powered DDR generator (Claude API + Streamlit) as a client-facing product – cut report
turnaround from hours to seconds, deployed with downloadable HTML/Markdown output.
Delivered routine and ad-hoc analytical outputs on sales and inventory data to improve operational decision-making and
forecasting accuracy.
Built analytical reports using Excel and SQL to monitor business performance and track key metrics for cross-functional
partners.
Performed trend analysis and demand forecasting on historical sales data to support inventory planning.
Improved data quality and reporting reliability through process standardization.
Supported strategic planning and business decisions using data-driven insights, presenting findings clearly to
non-technical stakeholders.