SUMMARY

• Data Scientist with 9+ years of experience in I.T. Industry in the areas of Data Science, Analytics, Business Intelligence and Data Warehousing Projects in multiple industries. Skilled in handling wide range of data and implemented intelligent solutions that created business value. Able to drive large and complex programs end - to-end, with focus on building competencies and providing direction.
• Capstone Project: Built a Pricing Optimization & Cash flow model which will help second largest waste management company in US to develop high impact pricing strategies, optimize the trade-off between price, risk, volume, and profit for the contracts they enter for residential solid waste collection business. This model will include sensitivity of input variables, calculation of NPV, EBIT & IRR and a multi period cash flow model for multi-period contracts.
• Performed Text Mining to find out meaningful pattern from unstructured textual reviews. Used R to search frequent words, examine frequency pattern across product categories, hierarchal clustering, and sentiment analysis
• Worked on Building predictive models for banking domain using R and Microsoft Azure machine learning platform for the problems such as Customer delinquency prediction using Logistic regression, Credit Risk Modelling Using Logistic Regression & Decision trees, Customer segmentation using K-Means clustering.
• Worked on building a recommendation system using Python language to recommend top books to new consumers using previous buying history and customer review on Amazon site of 548,552 different products. Applied concepts of text processing, network analysis and recommendation systems.
• Worked on a project in R language to predict the sales trend of future and to find out when to launch a new product of Tesla in Norwegian market. Using ETS method to decompose data to find out trend and seasonality effects in data and used exponential smoothing on it to forecast the future sales. Also, used Bass diffusion model to find out the external and internal effect to predict the time to launch a new model or product in market to keep the momentum of sales.
• Worked on Design of Experiment Project to determine the length of time it takes for ice to completely melt when placed in different type of solvent, different holders, and ice to liquid ratio. Used 3 3 factorial design in Minitab to do hypothesis testing, find statistically significant factors, interaction effects and regression equation to find the coefficients of each factors.
• Performing Data Cleansing, preprocessing, Dimensionality reduction, Exploratory Data Analysis using SAS, R, and Python.
• Experience in Big Data technologies and cloud computing such as AWS, Microsoft Azure, Hortonworks Hadoop ecosystem, Hive, Pig, Kafka, storm etc.

TECHNICAL SKILLS

• Data Management
• Data Mining
• Data Visualization
• Machine Learning
• Statistical Modeling
• Predictive Analytics
• Business Intelligence
• Fraud Analytics
• Project Management
• ETL
• Enterprise Data Modeling
• Pricing Optimization
• Software’s: SAS, R, Python
• Hadoop, Oracle,AWS
• Tableau, Cognos,SQL
• Microsoft Azure ML
• Erwin, Informatica
• IDQ, Planview, Appworx

PROFESSIONAL EXPERIENCE

Data Scientist

Confidential, AZ

Responsibilities:

• Created Machine learning models for credit risk modeling to find out the probability of loan default using SAS/R /SQL.
• Utilize machine learning algorithms such as logistic regression, multivariate regression, K-means, & Recommendation algorithms for data analysis.
• Working on building a regression model to predict the likelihood to pay after an account becomes delinquent.
• Performing Adhoc analysis to support collection operations using SAS and SQL which include evaluating the current operational strategies, enhancing the contact rate and early identification of potential large losses.
• Analyzed the data and created the Tableau dashboards to find out delinquency patterns of customers. Created reports with summarized and detail versions for identifying the aging stratification, trial balance, disposition changes and transactional detail for account receivables for Loan and Billing Systems.
• Prepared the data mapping sheet for the source to target mappings for data integration, aligned with data quality and transformation rules to integrate the client’s loan receivables data in Equiant Platform.
• Architecture ETL jobs to automate the process of loading the weekly files in Hadoop file system for multiple client sites.

Data Scientist

Confidential

Responsibilities:

• Designed successful state of the art Machine Learning models with high accuracy in SAS/R/Python Programming to predict credit card fraud using advanced statistical techniques such as Linear/Logistic regression, Decision treesand Dimensionality reduction
• Worked with source system developers, SMEs, Data administrators, Data integration team members to determine the data transformation method and required rule engine for fraud strategies implementation.
• Developed and improved fraud control strategies and validation of fraud rules using SQL and very high-volume application data by writing SQL queries to transactional databases.
• Worked on market segmentation analysis using cluster analysis techniques such as hierarchal clustering and K-means clustering.
• Worked on complex design of experiment (A/B campaign testing) for large marketing tests, developing marketing profit and loss models, statistical modeling of customer behavior, customer segmentations and managing strategic initiatives related to profitable growth in sales and assets.
• Managed teams effectively across different locations (Stamford, Mumbai & Noida) and done POC for clients.

Sr DataAnalyst Stamford, CT

Confidential

Responsibilities:

• Developed framework to move all financial close processes to the Last Calendar Day reporting schedule for Confidential Treasury to make it complaint with SEC and FED requirement.
• Analysis of feed from Treasury sub-ledgers, G/L inbound & outbound applications and prepared the business requirement documentation. Analyzed different subject areas which are involved in treasury data warehouse like Trade, Trading party, Cash flow, Mark to Market.
• Integrated multiple the application and underlying databases using ETL (Informatica) Mappings.
• Tuned the bottlenecks in ETL mappings using pushdown optimization, session partitioning and database partitioning, indexing etc.
• Worked on multiple Sources like Hadoop (accessed thru Hive), Oracle and MS SQL Server. Analyzed by writing complex queries and views in Hive using Hue and other sources and target.
• Increased project revenue by 100% through thorough scoping and resource assessment, establishing relationships early with client and understanding customer timeline requirements and goals.
• Managed team of 13 with project revenue of $1.2M, including development of multiple complex work streams, task prioritization and delegation by skills assessment.

Data Warehouse Engineer

Confidential

Responsibilities:

• Integrated Metreovision warehouse using ETL (Informatica) tool with Aviation MDM (Master Data Management) and designed the feeds of orders, revenue & backlog Data for top 10 aviation customers.
• Tuned the bottlenecks in ETL mappings using pushdown optimization, session partitioning and database partitioning, indexing etc.
• Tuned oracle SQL queries using table partitioning, indexing, joins and oracle hints.
• Created Reusable Transformations (Joiner, Sorter, Aggregator, Expression, Lookup, Router, Filter, Update Strategy, Sequence Generator, Normalizer and Rank) and processing tasks using Workflow Manager to move data from multiple sources into targets.
• Designed and built the services and quality dashboards using Tableau analytical tool to identify KPI’s, which helped to accelerate the dashboards availability process to take certain critical decisions on timely basis for Senior Leadership of Confidential Management business.
• Used Tableau to build an optimal solution which generated the required metrics and developed a reporting environment to enhance capabilities for faster, data driven commercial decisions.
• Analyzed and enhancedthe $3B monetization processusing Oracle SQL which essentially converts open Accounts Receivable into cash immediately to enhance cash flow and working capital balances.

DataWarehouse Engineer

Confidential

Responsibilities:

• Integrated data from existing legacy systems to GE EnergyData Warehouseusing Informatica as ETL tool. This included profiling of data, data cleansing, mapping of source data elements to new databases, design of staging area and normalized area.
• Integrated heterogeneous data sources with the help of Informatica (ETL) and build a reporting solution on the top of that using Cognos Cubes to provide slicing and dicing functionality.
• Analyzed multiple source systems using SQL queries and Stored Procedures, integrated them in a mapping and loaded into the Data warehouse.
• OLAP Dimensional modeling for very large systems using ERWIN tool, either in terms of the database size is in terabytes or in terms of creation of huge number of tables and indexes.
• Maintained the quality of data through high quality data model designs to ensure information integrity.
• Tuned the mappings developed in Informatica using Pushdown Optimization feature, partitioning, Incremental load etc. Worked on multiple transformations like Aggregator, Lookup, Stored Procedure etc.