
A Master's in Data Analytics programme helps students become proficient in a variety of technologies and abilities that are essential for success in the industry. I was able to advance my knowledge in Python, R, and SQL programming languages as well as statistical analysis, data visualization, and predictive modelling. Data mining, big data technologies (such as Hadoop and Spark), machine learning approaches, and tools for data manipulation and analysis (like Tableau or Power BI) were also covered in the course. Throughout the course, there was a strong emphasis on developing practical experience working with actual datasets, using analytical tools, and effectively communicating findings. I have undoubtedly emerged with a broad skill set that will enable me to take on challenging data problems in a variety of businesses.
Earning a bachelor's degree in mechanical engineering has equipped me with a diverse skill set and familiarity with a multitude of essential technologies, crucial for thriving in the engineering sector. My academic journey delved into an array of subjects including design principles and material sciences, with a particular focus on the dynamics of thermodynamics and mechanics. The curriculum also incorporated specialized courses like Problem Solving and Data Structures through C, Python Programming, Probability and Statistics, and advanced Mathematics, encompassing Linear Algebra and Calculus. A significant portion of my education was dedicated to mastering engineering software tools such as CAD and MATLAB, which are pivotal for design and analytical tasks. My proficiency in these applications was enhanced through hands-on projects, where I learned to evaluate and devise solutions for complex mechanical systems.
Predictive Analysis and Visualization of Plastic Pollution in North America
The 5 Gyres Institute (Non-profit), Boston, USA | Experiential Learning (Data Analyst)
• Collaborated with the 5 Gyres Institute to analyze 12 months of real-time data on plastic pollution in North America.
• Built a predictive model leveraging geospatial clustering analysis to identify top 10 geographic hotspots of plastic pollution.
• Visualized plastic waste data and built an interactive Tableau dashboard for stakeholder proposals.
Leveraging Sales Analysis and Predictive Modeling | Machine Learning, Regression, Hyperparameter optimization
• Utilized exploratory data analysis (EDA) techniques to understand customer purchasing behaviors and patterns.
• Deployed regression models, including Decision Tree Regressor, Random Forest, and XGBoost, to precisely forecast future sales.
• XGBoost model achieved outstanding results with an MSE of 1800.61, RMSE of 42.43, and an R-squared value of 0.92.
Laptop Price Prediction | R, Hypothesis Testing, Regression
• Performed comprehensive data analysis to make precise predictions regarding laptop prices.
• Established a laptop price prediction system using R, incorporating multiple linear regression, ridge, and lasso regularisation.
• The Lasso and Ridge regression models outperformed a basic Linear Regression model with R-squares of 75% and 76% respectively.
Yelp Data Analysis for Business Performance | Python, PySpark, SparkSQL
• Applied K-means algorithm for clustering analysis to extract restaurant distribution and characteristics from ratings and reviews.
• Engaged in an in-depth analysis of Yelp data to comprehend factors influencing businesses' success on Yelp platform.
• Deployed advanced big data tools for extensive analysis of a 5 million-record Yelp dataset.
As a master's student in Data Analytics at Northeastern University, I am passionate about using Python, SQL, and machine learning to solve real-world problems and generate insights from data.
I have 1+ years of work experience as an Assistant Systems Engineer at Tata Consultancy Services, where I enhanced data accuracy and optimized data workflows using Python for data processing and automation. I also collaborated with cross-functional teams to design and implement relational databases using SQL to store, manage, and retrieve financial data. Additionally, I have 3 months of internship experience as a Data Analyst at IkkatHub, where I leveraged advanced SQL queries, clustering and segmentation techniques, hypothesis testing methods, and Tableau dashboards to analyze and visualize sales data, resulting in a 7% increase in sales and a 20% improvement in data accuracy.