Arvind Kumar

Results-driven Data Analyst with hands-on experience building ETL pipelines, forecasting models, supervised Machine Learning models, and interactive Power BI, Tableau, and Streamlit dashboards. At Deloitte, consolidated data from 5+ sources to create a single source of truth, reducing data preparation time by ~40%, developed dashboards that cut report delivery time by ~50%, and implemented time-series forecasting models (Prophet/ARIMA) that improved forecast accuracy by ~12% — supporting a 6% cost-reduction initiative. Also built a Machine Learning regression model to predict academic performance, deployed via a real-time Streamlit dashboard.

Proficient in Python (Pandas, NumPy, Matplotlib, Scikit-learn), SQL, Power BI, and Excel; adept at translating complex data into actionable business insights.

Data Analyst at Deloitte (2026-01 – 2026-06)

• Designed and maintained ETL pipelines using SQL and Python (Pandas), consolidating data from 5+ sources into a single source of truth and reducing data preparation time by ~40%.
• Developed interactive Power BI dashboards and automated monthly reports for Finance and Operations teams, cutting report delivery time by ~50% and improving stakeholder access to KPIs.
• Built and deployed time-series forecasting models (Prophet/ARIMA) to predict monthly demand, improving forecast accuracy by ~12% and informing inventory and resource planning decisions.
• Automated recurring analyses and report generation using Python scripts and scheduled jobs, saving ~15 hours/week for the analytics team.
• Collaborated with business stakeholders to define key metrics, conducted ad-hoc analyses, and presented data-driven insights to senior management — contributing to a 6% cost-reduction initiative.

Data Science & Machine Learning Intern at Briztech Infosystems

Project: Student Performance Prediction System Using Machine Learning

• Engineered and trained a supervised Machine Learning regression model in Python and Scikit-learn to accurately forecast student academic performance.
• Streamlined data cleaning, feature engineering, and Exploratory Data Analysis (EDA) workflows on raw datasets using Pandas and NumPy, improving overall data quality for modeling.
• Deployed an interactive Streamlit dashboard delivering real-time performance predictions, enabling data-driven insights from key study metrics.

Bachelor of Computer Applications in Data Science & Artificial Intelligence – The ICFAI University, Ranchi (2024-08 – 2027-07)