SUMMARY:

• Around 8+ years of experience in data modeling, database design, programming, development and implementation of client - server application & data base systems using SQL server.
• Strong understanding of Relational Database Management System (RDBMS) including data model, tables, views, indexes, table space and partitioning etc.
• Extensive knowledge in business process reengineering of Fixed Income, Investment Banking, Foreign Exchange FX, Settlement, Accounting and Clearing of Securities.
• Experience in Finance, Retail, Investment Banking, and Insurance sectors.
• Excellent hands on T-SQL, SQL Server Integration Services (SSIS), SQL Server Reporting Service (SSRS), SQL Server Analysis Services (SSAS), SQL server.
• Extensive experience in conducting Market Research, Feasibility Studies, Data Analyses, Data Mapping, Data Profiling, Gap Analyses, Risk Identification, Risk Assessment, Risks Analyses, and Risk management.
• Experience in scripting T-SQL queries, complex stored procedures, user defined functions (UDF).
• Experience on creating SQL objects such as Tables, Stored Procedures, Triggers, Table valued parameters, functions, Views, Indexes, Relational Data Base Models.
• Experience in monitoring MS SQL server databases and performance tuning using Tuning Wizard, SQL Profiler and Windows Performance Monitor for Optimal Performance and resolve dead lock issues.
• Test & deploy code across various environments like DEV, Test, UAT and production.
• Expertise in configuring and creating SSIS solutions for ETL and Business Intelligence Process for Data Integration and Migration services.
• Responsible for the advancement and maintenance of data management operations within the Asset and Wealth Management line of business.
• Experience in managing and automating control flow, Data flow, events and Logging programmatically using SSIS packages.
• Highly proficient in the use of T-SQL for developing complex stored procedures, triggers, tables, user functions, user profiles, relational database models and data integrity, SQL joins and query writing.

TECHNICAL SKILLS

• Languages: Python and R
• Python and R: Numpy, Pandas, Matplotlib, Scipy, Scikit - Learn, NLTK, Seaborn, Keras, Tensorflow, Pyspark, Dask, Networkx, Beautifulsoup, Selenium, SciPy, ggplot2, caret, dplyr, purrr, readxl, tidyr, Rweka, gmodels, RCurl, C50, twitter, NLP, Reshape2, rjson, plyr, Rpy2, SAS, SAS V9.x /8.x, Base SAS, SAS/SQL, SAS/MACROS, SAS/STAT, SAS
• Algorithms: Kernel Density Estimation and Non-parametric Bayes Classifier, K-Means, Linear Regression, Neighbors (Nearest, Farthest, Range, k, Classification), Non-Negative Matrix Factorization, Dimensionality Reduction, Decision Tree, Gaussian Processes, Logistic RegressionNa ve Bayes, Random Forest, Ridge Regression, Matrix Factorization/SVD
• NLP/Machine Learning/Deep Learning: LDA (Latent Dirichlet Allocation), NLTK, Apache OpenNLP, Stanford NLP, Sentiment Analysis, SVMs, ANN, RNN, CNN, TensorFlow, Caffe, H2O, Keras, PyTorch, Theano,AWS sagemaker
• Cloud: AWS, Azure
• Web Technologies: HTML5, XML and CSS3,
• Data Modelling Tools: Rational Rose, ER/Studio, MS Visio, SAP Power designer
• Big Data Technologies: Hadoop, Hive, HDFS, MapReduce, Pig, Kafka, AWS EMR
• Databases: SQL, Hive, Impala, Pig, Spark SQL, Databases SQL-Server, My SQL, MS Access, HDFS, HBase, Teradata, Netezza, MongoDB, Cassandra.
• Reporting Tools: MS Office (Word/Excel/Power Point/ Visio), Tableau, Crystal reports XI, Business Intelligence, SSRS, Business Objects 5.x/ 6.x, Cognos7.0/6.0.
• ETL Tools: Informatica Power Centre, SSIS.
• Version Control Tools: SVM, GitHub
• BI Tools: Tableau, Tableau Server, Tableau Reader, SAP Business Objects, OBIEE, QlikView, SAP Business Intelligence, Amazon Redshift, or Azure Data Warehouse
• Operating System: Windows, Linux, Unix, Macintosh HD, Red Hat, Docker and Kubernetes

PROFESSIONAL EXPERIENCE:

Data Analyst

Confidential, Charlotte, NC

Responsibilities:

• Gathered requirements to customize ATG provided solutions, services, and ongoing guidance to power a more relevant and personal e-commerce.
• Involved in designing and developing Data Models and Data Marts that support the Business Intelligence Data Warehouse.
• Report to Director Wealth Management Technology and support the development and implementation of Wealth Management's technology roadmap.
• Utilized corporation developed Agile SDLC methodology. Used Scrum Work Pro and Microsoft Office software to perform required job functions.
• Partially involved in creating and maintaining data dictionaries for naming various object in the finance domain.
• Using Shared Containers and creating reusable components for local and shared use in the ETL process.
• Worked on creating and maintain sales reporting using in MS Excel queries, SQL in Teradata, and MS Access, produce performance reports and implement changes for improved reporting.
• Creating Excel templates created Pivot Tables and utilized VLOOKUPs with complex formulas.
• Provided weekly, monthly & ad hoc web analytics reports using Adobe Site Catalyst & Google Analytics.
• Worked on developing Tableau data visualization using Cross Map, Scatter Plots, Geographic Map, Pie Charts and Bar Charts, Page Trails, and Density Chart.

Data Analyst

Confidential, New York, NY May

Responsibilities:

• Strong knowledge of the Software Development Life Cycle methodologies like Agile, Scrum, RUP, and Waterfall models.
• Implemented Data Exploration to analyze patterns and to select features using Python SciPy.
• Built Factor Analysis and Cluster Analysis models using Python SciPy to classify customers into different target groups.
• Designed an A/B experiment for testing the business performance of the new recommendation system.
• Supported MapReduce Programs running on the cluster.
• Evaluated business requirements and prepared detailed specifications that follow project guidelines required to develop written programs.
• Participated in Data Acquisition with Data Engineer team to extract historical and real-time data by using Hadoop MapReduce and HDFS.
• Created SAS datasets by extracting data from various sources and used complicated data step logic
• Executed the SAS jobs in batch mode through UNIX shell scripts
• Created remote SAS sessions to run the jobs in parallel mode to cut off the extraction time as the datasets were generated simultaneously
• Reviewed and modified SAS Programs, to create customized ad-hoc reports, processed data for publishing business reports.
• Automated SAS jobs running on a daily, weekly and monthly basis using SAS/BI Unix Shell Scripting.
• Communicated and presented default customers profiles along with reports using Python and Tableau, analytical results and strategic implications to senior management for strategic decision making Developed scripts in Python to automate the customer query addressable system using python which decreased the time for solving the query of the customer by 45% * Collaborated with other functional teams across the Risk and Non-Risk groups to use standard methodologies and ensure a positive customer experience throughout the customer journey.

Confidential, New York, NY

Data Analyst

Responsibilities:

• Designed reports in Access, Excel using advanced functions not limited to vlookup, pivot tables, formulas
• Use SQL, PL/SQL to validate the Data going in to the Data Ware House
• Involved in Designing Star Schema, Creating Fact tables, Dimension tables and defining the relationship between them.
• Worked alongside team working on creating and schedule big data workflows in Spark, MapReduce, Pig scripts.
• Creating complex data analysis queries to troubleshoot issues reported by users
• Evaluates data mining request requirements and help develop the queries for the requests.
• Execution flows and Loading data to Netezza Data mart through NZLOAD utility.
• Experienced in handling Terabytes of records and manipulating them through SAS.
• Imported raw data files in excel format in SAS and subsequently created SAS Datasets and performed data manipulations on the datasets.
• Cleaned existing data and converted them into useful SAS Datasets, merged datasets and created reports based on Ad-hoc requirements.
• Extensively used PROC SQL and SELECT sub-queries to generate various reports by connecting to the Teradata DB.
• Used SAS Data Step logics to Sort, Merge, Stack, Update and Interleave datasets for producing required analysis of data and used SAS Business Intelligence (BI) to produce required Reports.
• Created various summary reports of POS, Total Sales, Regional Sales and Account Sales of various titles, regions and also presented the various sales reports using the Information Delivery Portal and the Dash Board Portlets.