Chandrava Das

CHANDRAVA DAS-, -, PROFESSIONAL SUMMARY Statistical Data Analyst with 6+ years of experience in building account management strategies, predictive models, descriptive analysis and statistical inferences for bank and financial institution using statistical tools and Machine Learning Techniques on SAS EMiner, SAS Enterprise Guide, Base SAS and SAS/SQL. Experience in team handling , mentoring , coaching and in advising corporations, managing clients and project delivery in the field of banking and finance catering to the North American and European Market. PROFESSIONAL EXPERIENCE EXL Service. Com (India) Private Limited (September,2020- Present) as Senior Manager Model Governance, Validation and Documentation Leading two major US Retail Cards portfolio with over 30 credit risk models based on decision trees Responsible for preparation of Model Development Document enlisting model usage, model technique of model inputs and outputs, trend summary, challenges of conceptual soundness for Risk Segmentation Models Preparation of Annual Model Review , monitoring performance and conducting detailed analysis of KPIs and trends of the strategies Provide actionable recommendations to the model Developers to improve the strategy performance Working closely with MRM team and ensure timely submission gratifying stipulated regulatory requirements Devise model change to tighten credit standards based on stress factor analysis to tackle projected recession in lieu of Covid-19 pandemic Checks the existing strategy and perform bad definition analysis for robustness of the model using Vintage analysis and Roll Rate Analysis HSBC Electronic Data Processing India Pvt. Ltd (February,2020- August,2020) as Manager Account Management Strategy Development for UK region Defining Requirements- Broad Objectives, timeline, milestones and requirements Data Preparation- Selecting the performance window, observation data, quality checks, variable extraction, validation sample data Segmentation, Profiling- Using CHAID in SAS EMiner, Segmentation Validation Monitoring of the New and Existing Strategies Data extraction, template creation, identifying KPIs, reporting KPIs. Adhoc Requirements Working on various Business Adhocs from time to time as per Business requirements Ford Motor Private Limited, Chennai (October, 2018 – February, 2020) as Senior Analyst Ford Motor Private Limited, Chennai (March, 2016 –September, 2018) as Analyst Scorecard development for FORD Credit, North America Region Prepare data set for Scorecard development Exploratory data analysis on the model development dataset by using Univariate data analysis, time series data analysis and other statistical tests to understand the data Using Machine learning techniques like decision tree, gradient boosting, random forest and variable clustering to select important variables for model development Selecting variables on basis of algorithms like information value and Gini-index Performing sigmoid function like Logistic regression to build originations scorecards to mitigate credit risk Analyzing the performance of the model built, by checking matrices like concordance, accuracy, ROC curve Out of time validation is done to see the stability of the model Developed both originations, collections and recovery scorecards Development of monitoring Scorecard performance dashboard Create an excel pivot view using SAS and excel to present business, where in to show the performance of the scorecard built. Use different matrices on basis of scores, segments, likewise to see the scorecard performance Quarterly analyzing Scorecard performance based on different metrics and recommendation by business Consultant for FORD Motor Company, India Analysis of Corporate Card Usage by Ford India employees Identifying areas of remarkable low usage of card Identifying potential areas where the card usage can be enhanced Using Decision tree for the analysis Suggesting and recommending business on observations As a part of Research and Development project Work on POC of implementing Machine Learning techniques in Scorecards Identifying the correct ML technique to be used Identifying the correct transformation for the technique which statistically significant and satisfies the business needs Used Gradient boosting techniques to fit the model Using different sampling techniques which will comply with the ML techniques use Tata Consultancy Services, Mumbai (July 2013 – February2016) as Senior Business Analyst Building predictive model to determine the drivers of pre-payment for different portfolios. Analyze data sets; perform statistical test like clustering, usage of non-parametric methods like decision tree and using business logic to determine the factors behind pre-payment. Using logistic regression in predicting the pre-payment of the portfolios. Retail analytics for a major US bank. Analyze the response and effectiveness of marketing campaigns for products like deposits, savings, debit cards, mortgage. Track and analyze trends and make appropriate recommendations Analyzing the success of the campaign by undertaking test of significance. Vintage Analysis to Study campaign results month over month. Study the customer transaction month over month. Silverline Business Consultancy and Research, Kolkata (April 2011 – June 2011) as Research Analyst Economic Research on Industry, Economy and Market. Quantam Consumer Solutions Private ltd, Kolkata (January 2011 –April 2011) as Freelancer Worked in the capacity of a Transcriber covering Interviews on FMCG sectors INTERNSHIP IMRB International, Kolkata (August 2010 –October 2010) as an Intern Understanding the market research problem and thereby carrying out survey for the target population. Data collection, cleaning and entry. Analyzing the data collected to understand the perception, motivation and expectation of the market. Project done on Legal process outsourcing (LPO), the idea was to examine and analyze the market sentiment about LPOs in Kolkata. TECHNICAL SKILLS Base SAS, SAS-EG, SAS-EMiner, SAS/SQL, Microsoft Excel, Visio, Word, PowerPoint, Oracle Hyperion, Putty. ACADEMIC BACKGROUND MSc in Economics from Madras School of Economics (2013) Post Graduate Diploma in Applied Economics and Information Management, from Globsyn Business School and University of Calcutta (2010) BSc (H) in Economics from Shri Shikshayatan College, Calcutta University (2009) Passed ISC (Class-12) in Economics, Mathematics, Statistics and ICSE (Class-10) from Sri Aurobindo Institute of Education, Kolkata in 2006 and 2004 respectively EXTRA CURRICULAR ACHIEVEMENTS Volunteer at an NGO “Make a Difference”- the responsibility includes teaching at shelter home Withinthe scope of CSR in the present organization part of the environmental awareness functionality As a part of CRS Activity, visited a rehabcenter for drug abusedchildren in Mumbai. Part of the Editorial team for college magazine “Athena”; member of the finance club “Alpha” Worked as a volunteer for “Light a lamp” (an initiative taken to educate the slum children); Vidyasagar (Teaching differently abled students); CRY- making the people of Suryanagar slum(Chennai) aware of the importance of schooling and thereby convincing them to send their children to schools. Certificates in dancing and painting.