SUMMARY

• B.E. with 14+ years of experience in Analytics & Consulting for Banking, Confidential, Retail and HR domains
• Expertise in Data Analytics, Business Intelligence, Research & Development, Machine Learning, Reporting & Market Research
• Expertise in the field of Risk & Collections Analytics, Digital Marketing, Customer Segmentation
• Developed PoCs (Proof of Concept) in Analytics domain with client stakeholders, and industrialized the solution across multiple offerings and capabilities
• Proficient in descriptive & inferential statistics using statistical software like SAS, Tableau, Python, Excel & SQL
• Knowledge of Univariate & Multivariate statistical techniques like Market Basket Analysis, Principal Component Analysis, RFM Analysis, CHAID, CART etc

TECHNICAL SKILLS

Statistical Tools: SAS, SAS - EG, SAS Macros, SQL, Python, SPSS, R-Studio

Visualization Tools: Tableau, Excel

Statistical Techniques: OLS Regression, Logistic Regression, Cluster Analysis, Decision Tree, Time Series

Machine Learning: Random Forest, Association Rules, Markov Chain, Naive Bayes

Others: SQL, Adobe-Insight, Windows XP, Mainframes, UNIX

PROFESSIONAL EXPERIENCE

Confidential

Manager

Technologies: Python, Excel

Statistical Methods: Time Series and Forecasting

Responsibilities:

• Analyzing data for retail client, fetching data insights and providing a better approach to client for increasing the revenue and profit

Confidential

Technologies: SAS, SQL, Excel

Statistical Methods: Logistic Regression

Responsibilities:

• Implemented a churn prediction model, to identify the key variables (products/revenue/etc) driving attrition across middle market, and implement necessary retention strategies
• Developed a churn prediction model on customer analytics using logistic regression, to understand consumer behavior and identify the parameters contributing to churning of VAS Services across Confidential client.
• The model is also scored against the future campaigns, to identify the customers from the top deciles, and implement various marketing strategies to prevent churning.

Network Analytics

Confidential

Technologies: Python, Tableau, Excel

Statistical Methods: Cluster Analysis

Responsibilities:

• Performed network analysis using cluster analysis for a leading Confidential giant
• Performed descriptive analytics for business reporting using Tableau and SAS, to generate insights and strategize the CRM campaigns
• Enhanced the workflow of value-added service (VAS) platform application and automated report templates thereby reducing 20 hours of manual effort per month

Multi-Channel Analytics

Technologies: SAS, SQL, Excel

Statistical Methods: Market Mix Modelling, Linear Regression, Log-Linear Regression, Log-Log Regression

Responsibilities:

• Market Mix Modelling for US based Bank to understand the impact of various promotion channels by incorporating marketing campaign data and sales data

Digital Marketing and Campaign Analytics

Technologies: SAS, SQL, Excel

Statistical Methods: Cluster Analysis, Association Rules

Responsibilities:

• Market Basket Analysis to create product association rules based on historical data
• Managed Real Time Web (RTW), E-Mail and Public site campaigns by tracking data from multiple sources, web site visits, calculating conversion funnels and identifying customer lifecycle
• Analyzed digital marketing channel & cross-channel campaign performance by creating performance dashboards with a focus on Web marketing effectiveness, KPIs & Trends identification
• Generated insights including trends identification & product detail into customers’ web & mobile behaviour to highlight areas of success or specific performance gaps within Digital Channels
• Managed Ad-hoc requests for Web Performance Analysis & provided actionable insights to optimize business KPIs and marketing ROI to the client for implementation

Collections Analytics

Technologies: SAS, Excel

Statistical Methods: Decision Tree, Linear Regression

Responsibilities:

• Built Logistic Regression Model to develop collections risk score by utilizing Bureau and internal PD for early and late stage delinquency buckets.
• Provided risk segmentation solution through advanced Decision Tree (CHAID & CART). Utilizing credit risk early warning triggers to develop a multidimensional solution for early & cost-effective treatment of delinquent accounts
• Created flexible collections strategies designed to overcome shortcomings of debtor-type models and improved customer retention by reducing the strain on debtors that are more likely to self-correct
• Maximized accounts receivable recovery by identifying accounts getting most benefit from collections efforts, and those more likely to pay during late stage collections
• Analyzed contact center agent’s efficiency to collect revenue and minimize roll rates & charge-offs by creating weekly, monthly, quarterly, prior 13 months, QTD, MTD & YTD time-period views
• Performed model validation on final reports with historical data to identify non-performing loans
• Generated business-friendly dashboards and reports highlighting trends in A/R Balances, Team & collection stage productivity for Credit Cards, Home Equity & Consumer Loans on monthly basis
• Analyzed Customers' Probability of Default (PD) by preparing Application & Behavioural Scorecard

Campaign Analytics

Technologies: SAS, SQL, Excel

Statistical Methods: Logistic Regression, RFM Analysis, Markov Chain

Responsibilities:

• Predictive Modelling, RFM Analysis for a US based Banker for Digital Marketing
• Developed a "Sales Demand" model by incorporating internal and external factors.
• RFM (Recency, Frequency and Monetary) analysis for customer segmentation to help in customer engagement strategy

Customer Profiling and KYC

Technologies: SAS, Mainframes

Statistical Methods: Decision Tree, Linear Regression

Responsibilities:

• KYC - Analyzed customer risk type profile by preparing application and behavioural scorecard
• EUMA - Analyzed customer loans data from multiple Banks
• CRS/FATCA - Created customer tax related reports from regulatory data mart (Bundesbank)
• Sales Channel Analysis - Analyzed customer's route to the bank through various channels

MIS Reporting and Dashboards

• Integrated new portfolios data into the regular reports and prepared ad-hoc analysis reports
• Automated processes by writing SAS Macros for data cleansing & manipulation of key metrics
• Created dashboards to understand how key business parameters are performing & trending over a period of time

Confidential

Designation: Software Engineer

Technologies: SAS, SQL, Excel

Statistical Methods: BI Dashboard, Feature Engineering

Responsibilities:

• Created HR Dashboards & Reports at various organizational levels viz. Total Segment, Region, Market, Area, Branch and Employee to understand and manage productivity levels
• Delivered following HR analysis using various analytical tools - Attrition Analysis, Competitor Analysis, Client Management, Adhoc costing analysis, Individual Billing & Cost Analysis, MIS Management, Trend Analysis, Work force Analysis, Segmentation, etc on monthly/ quarterly basis
• Analyzed performance & created scorecards on various measurable HR metrics, mapping of the requirements, workforce dashboards, Performance scorecards, developing capacity plan & utilization rates and metrics to ensure effective manpower planning
• Provided insights by preparing MIS reports on periodical basis to retain profitable customers, identified potential business client and communicated it to the business development team
• Identified data discrepancies and devised strategies for growth by analyzing market data, forecasting trends & projection through both quantitative & qualitative analysis
• Developed framework for client’s data analysis requirements, created & modified databases by writing queries & creating talent pipeline through various automation

Confidential

Consultant

Responsibilities:

• Analyzed the market potential under various parameters by way of primary research, revenue performance analysis, competitive profiling, and forecast analysis
• Collected, cleaned, managed, compiled, tabulated, manipulated data, analyzed the information collected, created trends and reports in HTML and Excel
• Experience in survey programming, questionnaire design & research analysis from available data
• Designed & executed students’ survey in colleges and analysis of engineering results using excel to underscore students' performance on the basis of different parameters