Business Analyst Intern
Highlights
Analyzed supply chain data using SQL to identify bottlenecks, improving outbound logistics efficiency by 10%.
Designed Power BI dashboards to visualize KPIs, enabling real-time decision-making for key stakeholders.
Automated reporting workflows to reduce manual effort by 40% and enhance data accuracy.
Utilized IBM Maximo for asset management and planning, improving coordination between logistics and maintenance teams.
Intern
Highlights
Collaborated with Toyota and MG workshops to optimize vehicle diagnostics and service procedures, developing a predictive maintenance model in Power BI that reduced downtime by 30%.
item Applied Kaizen and Six Sigma principles to enhance maintenance processes and uphold high-quality standards in vehicle repair and service.
Agastya, GDSC RVCE
Highlights
participated in Social Welfare Events like Paper Drive, Utsarga, Akshara, and Plantation Drive.
Mechanical Department
NPTEL
successful completion of course 'Design Technology and Innovation'
Python, C++.
Numpy, Pandas, Matplotlib.
GIT, MySQL.
Windows, Arduino, NodeMCU.
Operation Research and management, Supply Chain analytics, Product Life cycle.
Data Analytics, Excel, Power BI, SolidWorks, ANSYS, CNC Training, Machine Learning, IoT.
Summary
Analyzed AtliQ Mart's supply chain to enhance OTIF delivery metrics across three cities, track performance by city and customer, identify service gaps, and provide insights into popular product categories to improve operational efficiency.
Summary
Predicted surface metal defects using image inputs by training a supervised learning model on various defect types, enabling accurate predictions up to 90% for different user inputs. The model was trained on labeled datasets, allowing it to classify and identify defects based on new image data.
Summary
Analyzed eCommerce data to extract meaningful insights on customer behavior and sales trends, helping to drive better decision-making. Developed detailed visualizations that improved data interpretation, enabling stakeholders to quickly understand complex patterns and relationships.
Summary
Developed an IoT system for real-time gas leak detection, triggers safety measures such as cutting off power, activating exhaust fans, and sounding alarms. A mobile app was designed to provide real-time notifications, enhancing safety through prompt alerts.