PROFESSIONAL SUMMARY:

• Having overall two years of IT experience in entire SDLC life cycle as well as Data Engineer professional with over one year of experience in Data Science, Data Strategy, Data Mining, Statistical Analysis and Big Data Analytics in Financial Services, Banking, Web analytics and Telecommunications domains.
• Chartered Financial Analyst, Financial Risk Management with extensive working knowledge of Banking and Financial Services, Risk Management and IT services.
• Extensive experience in maintaining and analyzing all types of SQL databases. Adept at database management mining specific data from SQL information and working closely with departmental managers to create useful reports.
• Experience with Statistical Analysis and Machine Learning algorithms like Cluster Analysis, Association Rules, Linear and Logistic Regressions, Classification and Regression Trees, Naive Bayes, Text mining, Optimization, Bagging, Boosting, Random Forest, Neural Networks and Other Machine Learning algorithms.
• Working knowledge of Big Data concepts viz. Hadoop/HDFS and Map - Reduce with applications like HBase, Apache Spark and Microsoft Azure ML.
• Expertise in implementation of data science products using machine learning algorithms on AWS cloud architecture. Extensive expertise in statistical and analytics tools and languages like SAS, SQL on massively parallel architecture like Hadoop and Teradata.
• Experience with Big Data analytics and visualization tools like Tableau and Microstrategy 9 for dashboards and automation.
• Excellent analytical and problem solving skills and ability to work independently and as a part of the team.

TECHNICAL SKILLS:

Statistical Software: SAS (Base SAS, SAS/STAT, SAS/SQL, SAS/MACRO, SAS/GRAPH, SAS/ACCESS, SA/ODS)

Programming Languages: SAS, SQL, NoSQL, C, C++, .Net, MATLAB, Linux shell scripts, R and Hadoop/Big Data

Databases and Tools: Teradata, MS: Access, DB2

Environment: s: SAS 8, SAS 9.1, Windows 9x,2000, NT,XP, Linux

PROFESSIONAL EXPERIENCE:

Jr. Data Engineer

Confidential, Atlanta, GA

Responsibilities:

• Extensively used SAS and SQL for extraction, transformation and loading of data from Large Scale RDBMS like Oracle and DB2.
• Conducted data manipulation using merging, appending, concatenating and sorting datasets in SAS.
• Created several applications for the purpose of Statistical Modeling and Data mining using SAS/Base, SAS/SQL, SAS/Stat, SAS/Graph and also automated applications using SAS/Macros.
• Involved in administration of data warehouse using Warehouse Administrator functionality of SAS
• Design and development of different data models according to user specifications in the development of databases for small applications.
• Researched and studied Customer spending habits spanning several merchant categories and identified and formed a baseline for launching several merchant centric marketing campaigns and incentives and also resulted in the creating of Merchant Dashboard used by Product executives on a monthly basis.
• Created and implemented detailed Staffing Model for Security Solutions Business to evaluate and optimize internal and subcontractor staffing requirements based on the observed and forecasted backlogs, pipeline and historical demand analysis using time series forecasting, and optimization models.
• Operationalized and automated end to end staffing tool on the AWS cloud using R & Tableau in conjunction with the cloud architecture team to communicate model outputs and insights with business partners.
• Developed and implemented end to end analytics and machine learning pipeline for the Cloud compute and architecture organization within Disney’s Technology Solution and Services.
• Performed several Banking Center level performance analysis aimed at streamlining and optimizing the sales process and monitoring sales of certain high value checking products.
• Designed and implemented time series forecasting models for estimating server provisioning on the cloud environment which resulted in accurate demand forecasting for cost optimization and budgeting.
• Performed extensive data mining and exploration on the virtual and physical server performance log data and consequently applied anomaly detection algorithm using machine learning tools like R aimed at proactively determining performance issues and reducing downtime.

Technical Analyst Consultant

Confidential, San Francisco, CA

Responsibilities:

• Performed extensive Data mining on large scale Relational Databases like Teradata and DB2, having accessed, created and maintained detail and summary tables.
• Assisted in offering support to other personnel who were required to access and analyze the SQL database.
• Performed Path Analysis for measuring visitor drop rates and nodes with heavy bottlenecks to optimize customer experience.
• Adept at database management mining specific data from SQL information and working closely with departmental managers to create useful reports.
• Benefited and Helped in creating and presenting informational reports for management based on SQL data.
• Extensively used MS Excel pivot tables and MS PowerPoint for presenting results and making recommendations to Marketing and Sales teams and senior Executives.
• Helped in mining data from the SQL database that was used in several significant presentations..
• Performed extensive data quality analyses to evaluate existing data processes and recommended process fixes for accurately and effectively generate and measure data for analytics and reporting for leadership teams.
• Created and implemented automated data visualizations for tracking organizational KPIs by creating interactive visualizations and dashboards using Tableau and Micro strategy.
• Responsible for preparing the existing SQL platform for upgrades that were installed as soon as they were released.
• Created and maintained weekly and monthly Management Reports and Dashboard for senior management and Forecasting teams.
• Displayed high level of Project Management and communication skills by interacting with the Line of Business from inception and requirements gathering to presenting final results and suggestions.
• Conceived detailed modeling plan for developing customer value metric for identifying social influencers.