Aug 2020 – Sep 2020 · 1 mo · Remote

• Worked on real-world machine learning projects to build and optimize predictive models, enhancing my understanding of data preprocessing, feature engineering, and model evaluation techniques.
• Developed and implemented ML algorithms in Python, using libraries such as Scikit-learn, Pandas, and NumPy to analyze and manipulate datasets.
• Applied statistical analysis and data visualization tools (like Matplotlib and Seaborn) to interpret and communicate model performance and insights.
• Learned to fine-tune machine learning models using hyperparameter optimization techniques to improve model accuracy and performance.

Nov 2019 – Aug 2020 · 9 mos · Greater Delhi Area

• Skills & Knowledge Acquired:
• Python Programming: Gained proficiency in Python, focusing on libraries such as Pandas, NumPy, and Matplotlib for data manipulation and visualization.
• Machine Learning: Learned key ML algorithms including regression, classification, and clustering, and applied them on real-world datasets.
• Data Preprocessing: Mastered techniques for handling missing data, normalization, encoding categorical variables, and feature selection.
• Data Visualization: Developed skills in visualizing complex datasets using tools like Matplotlib and Seaborn, creating clear insights and presentations.
• SQL for Data Management: Strengthened my SQL skills to query, aggregate, and manipulate large datasets in relational databases.
• End-to-End Projects: Worked on hands-on projects that covered the full data science workflow, from problem definition to data collection, model building, and evaluation.
• Statistical Analysis & Model Evaluation: Applied statistical methods to validate data assumptions and evaluated models using metrics such as accuracy, precision, recall, and F1-score.
• Key Highlights:
• Worked on real-world datasets to implement machine learning algorithms and data processing techniques.
• Developed data-driven insights to guide decision-making through effective data visualization and analysis.
• Gained practical experience with the complete machine learning lifecycle: from data collection to model deployment.

Sep 2018 – Mar 2021 · 2 yrs 6 mos · Pune Division · On-site

• Built 10+ Tableau and Power BI dashboards used daily by 3+ business units for KPI tracking
• Performed data analysis and reporting to support business operations and decision-making processes
• Queried and optimized SQL on datasets exceeding 5M+ rows, improving query performance by ~40%
• Delivered weekly insights to 5+ stakeholders across operations and finance, directly influencing budgeting decisions
• Reduced manual reporting time by ~35% through automated SQL pipelines and standardized workflows
• Supported data engineering and ETL processes for structured and scalable reporting

Aug 2016 – Aug 2018 · 2 yrs · New Delhi Area, India