Technical Skills:
• Programming: Python: pandas, NumPy, Matplotlib, Seaborn, Sci-kit learn, Spacy, TensorFlow.
• Advanced Excel: Formulas, Power Query, Pivot Tables, VBA macros
• SQL: Commands, Joins, CTE, Stored procedures, User-defined functions, views.
• Visualization tools: Tableau: Calculation Fields Power BI: DAX, Dashboards, Reports.
• Finance: Financial Reporting and Analysis, Financial Modelling.
• Analytics: Statistics, EDA, Machine Learning, Deep Learning, NLP.

• Collecting 100+ M&A data points to provide actionable, reliable insights to S and P Global market intelligence clients
• Working on ML, Cloud-based collection tool(SPECTRA)

Relevant Coursework: Statistics for Business Analytics; BA for Decision Making; Predictive Analytics, Financial Reporting and analysis, Operations management, supply chain management, procurement management.

• Managed imbalance in data using three techniques and created a function to build Neural Network for each technique, which resulted in reduction of execution time by 80%.
• Visualized neural network, epoch accuracy, epoch loss using Tensorboard, leading to 50% less time in understanding performance of Neural Network.

• Devised a deep-learning model with 3670 images using CNN, improved model accuracy by 5 % using Dropout layer approach.
• Implemented transfer learning using a pre-trained model, which increased accuracy of model by 25%.

• Designed handwritten digit recognition model that extracts features (328 from 786) using PCA, and classifies the digits using Random Forest algorithm with 95% accuracy.