Technology Consultant - PricewaterhouseCoopers Service Delivery Center Private Limited (PwC) (June 2021 – Present]
Prepared the data for analysis and for further modelling through Exploratory data analysis (EDA).
Applied different Statistical models such as Naïve forecast, Simple average, moving average, Simple Exponential smoothing, Holt’s linear trend method, Holt’s winter seasonal method and Auto ARIMA and different Machine Learning models such as Linear Regression, Random Forest and XGBoost to forecast the sales data for a period of time.
Segmented the Customers based on Transaction data using k-means clustering to easily identify the top performing customers with the other type of customers who have high potential to move towards high performing customers.
Performed Churn Prediction using different ML models such as Logistic Regression, Decision Tree, Support Vector Machines (SVM) and Random Forest.
Achieved easier collaboration and version control by implementing all these models in Azure Databricks.
Hard skills
Technical Skills
Python (Pandas | Numpy | Matplotlib)
SQL
Time series forecasting
Clustering
Exploratory Data Analysis (EDA)
Microsoft Azure (Azure Data Factory (ADF) | Azure Synapse Analytics)
Databricks
MLflow
Tools
Jupyter Notebook
PowerBI (Basics) | Alteryx (Basics)
Soft skills
Achievements
Awardee | Prime Minister Scholarship Scheme | Ministry of Defense, Government of India
Selected as one among 2600 students all over India for academic Excellence to avail INR 27,000 per year for four
consecutive years of the undergraduate studies.
Graduate Aptitude Test in Engineering (GATE)
Qualified GATE Computer Science and Engineering in which only around 15% of the appearing candidates qualify each year.
