SHUBHAM KSHIRSAGAR
******************@*****.*** LinkedIn GitHub +1-804-***-**** Virginia, United States Open to relocate MSBA 5+yrs Experience Data Science Business Analysis Machine Learning Business Intelligence Data Visualization
PROFESSIONAL SUMMARY
Passionate Data Analyst adept at transforming complex business challenges into actionable insights. Proficient in advanced machine learning techniques. Expert in agile methodologies, fostering cross-functional synergy to drive data-centric decisions. Excels in translating technical insights into business value, ensuring stakeholder support.
EXPERI ENCE
Senior Data Analyst - NVIDIA August 2021 - July 2023
Analyzed business challenges, implemented predictive analytics, and optimized data retrieval processes, achieving a 10% reduction in delivery times and $50,000 annual savings in operational costs.
Led data engineering optimization using SQL and Python for web scraping, deploying on AWS EC2, and storing data on AWS S3, improving workflow efficiency by 25% and saving 200+ work hours annually.
Facilitated improved coding practices through code maintenance, technical guidance, and knowledge sharing, achieving a 20% efficiency boost that expedited project delivery by 2 months.
Studied past customer behaviors and predicted future trends by developing robust ML models and conducting thorough hypothesis testing, improving credit performance by 7%.
Spearheaded data analysis projects using Jira, managing user stories and tasks, streamlining communication and collaboration across technical teams, resulting in a 15% reduction in project turnaround times.
Engineered demand Time series forecasting models using data from AWS Redshift, boosting prediction accuracy by 25%. Optimized pricing strategy, leading to a 5% increase in profits.
Conducted in-depth data analysis of e-commerce product pricing and market dynamics, leading to the development of a pricing optimization strategy that increased revenue by 12% beyond expectations.
Orchestrated root cause analysis and Ad Hoc reporting in Power BI, building data models that increased predictive accuracy by 20% and decreased issue resolution time by 25%, optimizing business strategy and decision-making.
Data Analyst - NVIDIA October 2017 – August 2021
Leveraged data science techniques to enhance data usability by 25% during EDA, extracting insights using statistical analysis that improved customer satisfaction scores by 20%.
Created effective marketing strategies by analyzing customer needs and preferences through data mining and data-driven analysis, resulting in a 10% increase in sales and enhanced customer engagement.
Directed metadata management and leveraged GitHub for version control, achieving a 20% boost in data processing efficiency and saving over 200 annual work hours.
Utilized Alteryx to create ETL pipelines of complex dataset, enhancing business intelligence reporting accuracy, and Tableau for analysis, leading to a 15% increase in actionable insights for strategic business decisions.
Delivered 18% greater efficiency on customer behavior data to personalize product recommendations through clustering analysis and other ML models, identifying a 12% increase in product adoption rates.
Developed and managed data warehousing solutions to streamline operations, automate reports, and track KPIs, resulting in a 20% improvement in operational efficiency and more timely decision-making.
Designed interactive Power BI dashboards to present insights to stakeholders in ad-hoc forums, resulting in a 15% increase in data-driven decisions and a 10% growth in quarterly revenue.
TECHNICAL SKILLS
Python, R
SQL
Alteryx
Tableau
Power BI
AWS- Redshift, S3
EC2, DynamoDB
Glue, Athena
ML Techniques
Jira
ETL pipelines
ERDPlus (Schema)
Statistics-A/B testing
MS Office, Excel
Git, GitHub
EDUCATION
William and Mary - Raymond A. Mason School of Business, US August 2023 - May 2024
Master of Science in Business Analytics- Data Science
Nagpur University, India August 2013 - August 2016
Bachelor of Engineering - Electronics and Telecommunication
PROJECTS
Amazon Sales Analysis- Analyzed and visualized Amazon sales data using Tableau to identify revenue trends, optimize sales channels, and enhance regional profit strategies.
Car Crash Detection Model- Implemented ML models such as logistic regression, random forests, & bagging in R.
Airbnb Listings- Python script uses Selenium package to navigate and scrape data from Airbnb's website.
Stock Analysis- Combined data manipulation, visualization, and interactive APIs in a Python script.
Superstore Analysis- Designed an interactive Power BI dashboard focusing on time series analysis, to provide valuable business insights and accurate sales forecasting.