Debayan Daw

Experience

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  Deepalaya

  Oct 2013 - Jan 2014

  Volunteer

  Worked as a volunteer in the field of Education of girl child- Involved in teaching of basic computer and English to the students- Involved in art and craft activities and documentation work- Participated in community awareness programme for Deepalaya

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  Mu Sigma Inc.

  Feb 2014 - Oct 2015

  Trainee Decision Scientist

  Worked as a Trainee Decision Scientist with one of the largest e commerce retailers in U.S.- Worked on the descriptive analysis of customers to understand the visitation behavior of the most loyal customers- Built a long range planning tool to predict the output scenarios of customers, revenue, spend per customer and frequency based on various input parameters- Worked on customer segmentation using methods like k-means and classification of segments into different personas based on transaction, visitation and psycho-graphic behavior of customers- Built a subscription tool to understand the customer adoption based on market segments and projected adoption rate by marketing channel - Comprehensive database management and migration from Greenplum to Teradata- Conceptualized and designed a dashboard to measure the effectiveness of email marketing vehicle on a monthly and yearly basis- Have done numerous adhoc analysis to help the clients understand the overall performance of their business-Tools/Languages Used: PostGreSQL, SAS, R Shiny, Python, Hive, Excel, VBA Show less

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  EvolvAlytics Consulting Pvt Ltd

  Dec 2015 - Oct 2016

  Data Analyst

  Client: Leading supplier of engineered equipment and systems in Chemical and Pharmaceutical markets in India- To determine the sales strategy of the company- Determined the key KPI’s defining the sales of the company- Segmented the customers base based on the key KPIs- Market Basket Analysis to determine the right combination of products to be used for sales strategyClient: Leading Off the Road Tyre Manufacturing Company in India- Collation and cleansing of past 3 years’ sales and product demand forecast data- Descriptive analysis to understand the business trends across SKUs as per projects- Data analysis for minimizing on Forecast Errors leading to better Inventory Management - Graphical understanding and representation of data using Tableau softwareBusiness development - Made point of view for different projects to the healthcare client and leading engineered system client Show less

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  The Smart Cube

  Nov 2016 - Aug 2019

  Senior Analyst

  Sentiment analysis (Product)- Built a model to predict whether a sentiment is positive or negative using amazon product reviews and twitter sentiments data along with glove vector embedding- Achieved an accuracy of 85.34% using LSTM model- Tools and Algorithm: Python, LSTMCross sell model across products (Gaming industry)- Created a cross sell model to identify players who are going to play a certain game, if they have not played it for some time period- Built campaign framework to cross sell the products based on drivers and identify the right set of players- Tools and Algorithm: Python, SQL, Random forest, Logistic regressionWallet load analysis (Gaming industry)- Built a model to identify players who are going to load the wallet in the next week- Undertook the analysis to understand the player’s behavior towards missing out on wallet load and thereby targeting players with the right campaign at the right time- Tools and Algorithm: Python, SQL, Random Forest, Logistic regressionCustomer lifetime value model (Gaming industry)- Determined the revenue that a player is going to bring in his entire engagement with the client- Built a survival model to get the probability of his survival for his entire future journey- Created different segments based on CLV and defined strategies for each of the groupsMarket mix modelling (CPG: Beverages)Built a market mix model to understand the impact of different marketing levers on the sales volume using Nielson, media and trade data for Saudi Arabia regionAlso, defined the optimal price strategy for the product and did category forecasting for the productTools and Algorithm: Python, Excel- Tools and Algorithm: Python, SQL, linear regression, coxph algorithm Show less