Acquisition Risk - New Account Offer Generation (Pre-Screen)

I worked as a Data Science intern in the Machine Learning department and worked on three projects during my time here:1)Prediction of price of 2 particular grade of crude oils using LASSO regression and ARIMA model for Time Series forecasting, using the data pertaining to supply and demand (grouped according to regions), expected GDP growth, financial factors, seasonality and exchange rates.Tools used: Excel, Python, Tableau.2)Sentiment Analysis of customer emails sent to a… Show more I worked as a Data Science intern in the Machine Learning department and worked on three projects during my time here:1)Prediction of price of 2 particular grade of crude oils using LASSO regression and ARIMA model for Time Series forecasting, using the data pertaining to supply and demand (grouped according to regions), expected GDP growth, financial factors, seasonality and exchange rates.Tools used: Excel, Python, Tableau.2)Sentiment Analysis of customer emails sent to a select group of business managers into Positive, Neutral, Negative and Extremely Negative using various NLP libraries in Python. Extensive data cleaning formed a large part of the project.Tools used : HTML, Excel, Python.3)Optimization of internal bus network in thee corporate park so as to schedule an optimum number of Buses and golf carts running throughout the day at appropriate gates within the complex and at particular timings.Factors like the mean number of employees arriving at all gates at a particular time, their punch in times at respective buildings and preferential mode of transportation of employees was taken into consideration.Tools used were Python and Gurobi. Show less

• Using historical data, research and anecdotal information by collaboration with higher management, sales teams and retailers to create multiple forecasts in scenarios with different requirements for production, shipping and credit by using various time series methods and using errors from previous forecasts to continuously improve the model.• Monitoring various lines of production to ensure efficiency to meet demand of the customers in a timely manner.• Prepared reports of forecasts… Show more • Using historical data, research and anecdotal information by collaboration with higher management, sales teams and retailers to create multiple forecasts in scenarios with different requirements for production, shipping and credit by using various time series methods and using errors from previous forecasts to continuously improve the model.• Monitoring various lines of production to ensure efficiency to meet demand of the customers in a timely manner.• Prepared reports of forecasts and warehouse inventory for upper management using Excel and Tableau and suggested ways to improve efficacy.• Executing a quality project to increase the average ultimate tensile strengths of by 0.42%, using statistical control charts, design of experiments and ANOVA, in order to support critical operations of Key clients.• Devised a random sampling methodology to test product specifications against a set critical quality standard. Show less