Data Analyst Intern — Corizo

Sep 2023 – Jan 2024 | Hyderabad, India (Remote)
During my internship at Corizo, I worked extensively on data analysis and insight generation for operational teams. My role focused on improving the quality, usability, and decision-making value of data across the organisation.

Key Contributions:

• Analysed, cleaned, and processed large datasets to ensure high data integrity, directly contributing to a 10% improvement in operational decision-making accuracy.

• Collaborated with cross-functional teams to design efficient data preparation workflows, transforming raw inputs into structured, analysis-ready datasets. This improved usability and reduced data preparation time by 25%.

• Developed clear, actionable insights that supported strategic planning, resulting in a measurable 12% increase in overall operational efficiency.

• Worked with SQL and data visualization tools to support ongoing analytics and reporting needs.

Data Science Intern — Rubixe (AI Solutions Company)

Apr 2023 – Jul 2023 | Bengaluru, India (On-site)
At Rubixe, I contributed to the development of analytics and machine learning solutions for client-facing AI products. My work involved hands-on data analysis, modeling, and workflow optimization.

Key Contributions:

• Used Python, Pandas, and Scikit-learn to perform Exploratory Data Analysis (EDA) and build machine learning models that enhanced predictive accuracy by 20%.

• Improved internal workflows by collaborating on data preprocessing pipelines, reducing noise, improving data quality, and boosting analytical efficiency by 30%.

• Supported the design and implementation of predictive analytics for client inventory management systems, leading to a 15% reduction in excess inventory.

• Conducted experiments through Jupyter Notebooks, documented findings, and communicated insights to senior data scientists and product teams.

DevOps Intern — Prodevans

Jan 2022 – Jul 2022 | Bengaluru, India (Remote)
As a DevOps Intern, I worked on cloud architecture, automation, and scalable system design using Amazon Web Services (AWS). My focus was on improving system performance, uptime, and operational efficiency.

Key Contributions:

• Built and maintained scalable cloud-based solutions using AWS and Python, increasing overall system scalability by 25% and reducing deployment time by 40%.

• Engineered robust cloud architectures designed to support high-performance applications, achieving 99% uptime in live production environments.

• Designed serverless solutions using AWS Lambda, enabling efficient microservices and reducing operational costs by 20%.

• Gained hands-on experience with Docker, CI/CD pipelines, and infrastructure automation, contributing to reliable and cost-effective deployments.