Team Lead/ Sr. Analytics Lead Resume
- 10 years of Professional Experience in Data analysis, Database marketing, Customer profiling, SAS Programming, Statistical Analysis and modeling, Credit scoring, RFM analysis, Text Mining, Pattern Recognition and Web Analytics
- Base/Advanced /Predictive Modeler SAS Certified programmer/analyst with around 10 years of experience in Analysis, design, development, testing and validating the applications
- Experience with credit card, debit card, banking, retail and health care data
- Experience in creating thoughtful analytics to address business issues and independently generated forward - looking solutions using Tableau/Power BI/AWS QuickSight
- Functional knowledge of risk management principles and credit card terms within Financial services industry
- Experience in building Risk score models for controlling Fraud and increase the customer traffic
- Experience in creating and automating daily, weekly, monthly, Profitability analysis reports for credit/debit card products
- Experience in analyzing the data for Direct Mail Campaign’s, Former customers, new customers, ITA (Invitation to Approval).
- Experience in various advance SAS Tools such as Clustering and segmentation, self organizing maps(SOM) Kohonen, Support Vector Machines (SVMs), Two stage models, component models, customer attrition and churn models via survival analysis, credit scoring models, Customer Lifetime Value (LTV) Analysis, Text Mining and basic SAS tools such as Regression (Linear, Logistic), Decision Trees, Neural Networks, GLM, Gradient Boosting, Memory Based Reasoning (MBR), RFM Analysis, Time Series Analysis, t-test
- Proficient in the following reporting and statistical procedures: REPORT, SQL, APPEND, DATASET, TABULATE, FREQ, MEANS, UNIVARIATE, TTEST, CORR, PRINT, REG, GLM, ANOVA, IMPORT, SUMMARY, LIFETEST, TRANSPOSE, COMPARE, EXPORT, COPY, CONTENTS.
- Experience in using SAS to import/export data to external file formats like flat, Excel, XML files
- Experience in Data Extraction, Transformation, Loading, Analysis, and MIS Reports for Banking.
- Created complex and reusable MACROS, extensively used existing macros and developed SAS Programs for Data Cleaning, Validation, Analysis and Report generation. Tested and debugged existing macros.
- Experience in the BI Suite in SAS including SAS Enterprise guide, SAS OLAP Cube Studio, SAS Web Report Studio, SAS Data Integration Studio and Information Map Studio.
- Experience with SAS Business Intelligence Platform: SAS add-in for Excel, Web Report studio, Dashboards, JMP
- Experience in utilizing statistical software packages (SAS, R, IBM SPSS Modeler, Tableau, and Rapid Miner) to summarize data, perform analysis, and model building.
- SAS Metadata and ETL developer with extensive knowledge of building & implementing metadata repository & metadata security.
- SAS ETL developer with expertise in design and development of Extract, Transform and Load processes for data integration projects to build data marts
- Experience in developing SAS codes using SAS Enterprise Guide and SQL queries in SAS for creating stored processes using the dynamic prompts containing both packaging and streaming output, and prepared reports using ODS.
- Experience with SQL programming and reporting.
- Proficient in RDBMS design and development different Databases like Oracle, SQL Server, DB2 and Teradata
- Exposure on every step of entire software development life cycle (SDLC) including data collection, query, modifying and analysis, coding statistical models, summarizing the findings, and presenting the results.
- Ability to work efficiently in both independent and team environments, worked with Project Managers, Team Members / Associates, Statisticians, Business Analysts.
- Good understanding of Data Warehouse concepts including Star Schema and Snow-Flake Schema
- Strong Problem Analysis & Resolution skills and ability to work in Multi Platform Environments like Windows and UNIX
- Experience in creating test cases to make sure the data originating from source is making into target properly in the right format.
SAS Tools: Base SAS 9.3/9.2/9/8.2/8.1/6 (mainframe), SAS/Stat, SAS Macros, SAS/SQL, SAS Graph
Reporting Tools: Base SAS versions 9.3/9.2/9/8/6, SAS Enterprise Guide, SAS Enterprise Miner, SAS Graph, MS-Excel, SAS BI Platform, SAS OLAP Cube Studio, SAS Web Report Studio, MS-VISIO, and MS PowerPoint
RDBMS: SAS SQL, DB2, Oracle 7x/8i/9i/10g/11g, Teradata, MS-Access, Microsoft SQL Server, and MySQL.
Languages: SAS, SQL, C, C++, C#, Java, Visual Basic, Visual C++, PHP Operating System Windows 95/98/XP/Vista/Win 7, UNIX, MAC OS, and DOS. Batch Server UNIX, Putty, SSH, and SAS scripting.
Web Server: HTML, JSP, Linux, Apache Server.
Office Tools: MS-OFFICE, Word, Excel, PowerPoint, MS ACCESS
AWS Services: Amazon S3, RedShift, Amazon Aurora, QuickSight, SageMaker, AWS Glue(ETL), Amazon Athena Python Pandas, NumPy, scikit-learn, PyCaret, Matplotlib, WordCloud, Pulp, Pandas Profiling, Keras ML Techniques Feature Engineering, Scaling/Normalization, Identifying Correlated Features, Outlier Detection, Imputations ML Algorithms Regression, SVM, Random Forest(Bagging/Boosting), Naïve Bayes, K-Means, KNN, XG Boost, NN
Soft Skills: Team Leadership, Problem Solving/Critical Thinking, Going Above and Beyond, Decision Making, Multi-tasker, Attention to detail
Team Lead/ Sr. Analytics Lead
- Extraction of data from Oracle, created into datasets.
- Provide data analysis to assist the business with developing critical strategy and addressing business issues
- Assist with complex data analytics and data modeling from end-to-end, including designing and developing segmentation strategies for retail and credit card collection.
- Perform hands-on data analysis, including data extraction, sampling, and trending to monitor the health of the collections recovery environment.
- Develop tests to determine the effectiveness of new ideas, as well as targeted strategies based on data analysis and testing to improve overall effectiveness of the collections recovery business.
- Assist with development and implementation of key processes that directly impact the overall performance of network collections recovery for the Credit Card and Retail businesses.
- Recognize opportunities and enhancements to existing models to improve overall financial performance, customer experience and execution quality.
- Partner with internal groups to build or modify strategies to improve liquidation and overall performance including regulatory and compliance aspects.
- Conduct ad-hoc analytics to address business issues and generate forward-looking solutions. Explore new data sources and cross line of business (LOB) collection best practices to drive the business forward
- Coding SAS programs with the use of Base SAS and SAS/Macros for ad hoc jobs.
- Participated in marketing campaign-planning meetings with program managers in order to develop and document campaigns specifications
- Performing data validation, transforming data from RDBMS oracle to SAS datasets.
- Involved in extracting, analyzing and auditing marketing data from the data-warehouse using SAS
- Analyze credit data to estimate degree of risk involved in extending credit or lending money to firms or individuals, maintain credit file documentation and interact with customers as a secondary contact with the officer.
- Prepare financial data for analysis of creditworthiness of customers measured with cash flow, liquidity, financial positions and trends, industry risk and secondary sources of repayment for use sales for lending products such as business and personal lines of credit, installment loans, commercial and residential real estate, unsecured lending and asset-based lending
- Develop business strategies (to include - line management, reissue, authorizations, risk based pricing and new application automation) that deliver measurable profitable growth.
- Perform business analysis and report to understand financial performance by risk and key channel and partner sub- sectors that will be used to inform future investment decisions
- Optimize the risk and reward balance by applying and assessing the NPV performance across the various portfolio segments
- Designed comprehensive design specifications to facilitate creation of ETL programs.
- Prepared and tested ETL codes as part of SAS projects.
- Coordinating the production of monthly, quarterly, and annual performance reports for senior management
- Transformations using Base SAS Procedures & Functions.
- Responsible for the cleaning, reformatting, analysis and loading the data into the database.
- Maintaining and enhancing existing SAS reporting programs for marketing campaigns.
- Maintaining SAS statistical analysis for the products purchased every month.
- Run reporting programs and download the results into EXCEL and build pivot tables.
- Developed SAS MACROS for reduction of program length and for faster execution.
- Modifying incoming data using SAS code by reformatting, importing, sorting, merging and restructuring
- Creating permanent formatted SAS data sets and developed reports using PROC REPORT, PROC TABULATE and DATA NULL for analysis.
Environment: Base SAS, SAS/Macros, SAS/Access, SAS/Connect, SAS/Stat, SAS/Graph, SAS/SQL, SAS/ODS, Oracle (TOAD), PL/SQL, MS Excel, SAS Enterprise Guide, SAS Enterprise Miner, Python, Tableau and UNIX, AWS
Confidential, Horsham, PA
Sr. Data Science Analyst (Partner Card Analytics)
- Ability to wrangle large datasets, structured and non-structured data, including data mining and manipulation
- Demonstrated understanding and experience with technical systems, datasets, data warehouses, data analysis techniques and data visualization using Tableau/Power BI
- Knowledge of consumer auto lending / leasing portfolio preferred
- Ability to design and implement process documentation and monitoring protocols, demonstrated understanding and experience with technical systems, relational and dimensional datasets, data warehouses, and data analysis techniques
- Strong quantitative, analytical and data interpretation skills
- Ability to summarize complex data into digestible information for management
- Uses appropriate programming languages (Python, SAS, R) to develop business and operational reporting and data visualizations that enable effective and efficient decision-making
- Builds technical knowledge to support research and analytic responsibilities through independent learning
- Maintains thorough understanding of relevant data sources and metrics
- Analyzes key metrics and performing data analysis
- Leads work with IT and key business units to identify opportunities and inconsistencies in data and develops long term solutions for data capture and maintenance and serves as a subject matter expert
- Extracts meaningful insights and trends and makes recommendations for various analyses to senior leadership which will improve business performance
- Partners with and provides recommendations to business leadership on the appropriate application of analytics to business strategies and effectively communicates analysis and implications to senior leadership
- Serves as a technical and analytical mentor to less experienced analysts
- Ensures that the delivered products meet the business needs of the company
- Prepares data for conversion through data mapping, translation rules, and cleaning.
- Performs tests to ensure smooth data transition between systems.
- Executes data extraction programs/data profiling and analyzes data for accuracy and quality.
- Maps data and data relationships, validates population of cubes, stars and marts and accountable for most efficient data flows.
- Gathers and analyzes data requirements and validates complex data models ensuring ability to enable requirements
- Work with business users & source system experts to understand analytical and reporting expectations, underlying source data and associated business rules
- Work within an agile environment to understand business expectations and prepare user stories and acceptance criteria for consumption by the sprint teams
- Use SQL to analyze source data, identify data quality issues and understand how the data matches business processes
- Document, articulate and explain technical issues in simple, straightforward ways that are understandable by technical as well as non-technical stakeholders
- Develop and execute quality assurance and test scripts. You'll be work with product owners and business analysts to understand business requirements and use cases to design solutions.
- Present persuasive information in varying technical depth to different audiences
- Lead requirements gathering meetings with high level executives as well as front line employees
- Communicate effectively within a geographically diverse company, both within the immediate team and with business users across the organization
- Be a promoter of enterprise standards around data and data processes and a role model for a data driven culture
Environment: Base SAS, SAS/Macros, SAS/Access, SAS/Connect, SAS/Stat, SAS/Graph, SAS/SQL, SAS/ODS, Oracle (TOAD), PL/SQL, MS Excel, SAS Enterprise Guide, SAS Enterprise Miner, Spotfire, Tableau and UNIX
Marketing Campaign Research/Database Analyst
- Participated in marketing campaign-planning meetings with program managers in order to develop and document campaigns specifications
- Provides actionable overall market and customer insights to address key strategic questions.
- Responsible for tracking, reporting, and analyzing the performance of marketing activities, ad-hoc analytic requests, and development/automation of regular reports.
- Analyzes external and internal customer data using database queries (SQL, Access), spreadsheet (Excel) models, web analytics tools (Adobe / Omniture), statistical analysis tools, and campaign management software tools.
- Evaluates customers’ online behavior and provide insights and recommendations for further enhancements to the guest experience.
- Analyzes A/B and Multi-variate tests, communicate results and provide recommendations.
- Creates PowerPoint presentations to provide market and consumer insights to other marketing and sales departments.
- Advises other marketing functions (e-commerce/website, online/offline advertising, brand, product development) as the knowledge owner for customer and market data
- Designing multiple analysis and modeling disciplines and processes and expertise in best practices for analytical modeling and analysis. Preferably in one or more of the following: risk management, computational finance, or forecasting / valuation models
- Design, develop, implement, and maintain productivity tracking, performance monitoring, financial, and other production-support related reporting to support business MIS needs.
- Demonstrated ability to effectively manage all facets of the analytical project lifecycle (data discovery/exploration, hypothesis testing code development, testing/validation, model deployment, etc.)
- Hands-on experience with a wide variety of predictive modeling, machine learning, data mining, statistical/text mining, and optimization algorithms
- Perform data mining and complex analyses to support enhancements of program credit qualification criteria, and track performance of the balance stimulation program and various tests.
- Conduct quantitative analysis to identify business opportunity through all phases of analysis - pulling data, ensuring data integrity, synthesizing and communicating findings to senior executives.
- Track performance of initiatives against expectations. Provide insights based on analytic findings, ranging from loss forecasting using risk appetite framework to strategy development.
- Proven ability to perform quality control checks during the model/analytical solution development lifecycle
- Liaise with default and retention operations departments to determine business reporting needs, following the spirit of the SLDC.
- Utilizing data analysis tools including Microsoft SQL Server Developer, SAS 9.2 (PC and UNIX including rsubmit), Microsoft Access, Microsoft Excel, and IBM DB2. Work on a UNIX server to develop, test, and implement SAS-based reporting scripts.
- Utilizing the SAS Output Display System, specifically the EXCELXP tagset to create customized specific reporting.
- Utilizing SAS Internet to create user query-able reporting products.
- Involving in the administration of the enterprise data warehouse using warehouse administrator.
- Writing SAS code for developing data sets from raw data files received in text format. This included cleaning data.
- SAS/ENTERPRISE GUIDE software was used for file and program management purposes.
- Connecting to Oracle and pulled data into SAS data sets using SQL pass through facility.
- Creation of macros to automate the code so that they generate reports on the invocation of the macro which helped to save time and manual intervention.
- Extracting transforming, and loading data using SAS/ETL.
Environment: Base SAS, SQL, PL/SQL, Teradata, Netezza SQL assistant, Mainframes, UNIX, SAS, Visual Basic, SAS/EG, SAS Warehouse, SAS Enterprise Guide, SAS Enterprise Miner, JMP, Spotfire
Confidential, Atlanta, GA
- Developing programs & Statistical analysis of product sales, performance of Sales department, forecasted regional sales, Monthly, Quarterly and Yearly sales reports. The incentive compensation was taken care of in this project and the profit forecast was also done
- Creating permanent formatted SAS data sets and developed reports using PROC REPORT, PROC TABULATE AND DATA NULL for analysis.
- Developing and applying mathematical or statistical theory and methods to collect, organize, interpret, and summarize numerical data to discover useful information.
- Designing, developing, implementing and validating statistical models and segmentation strategies for the bank’s card risk, Comprehensive Capital Analysis and Review, loss reserve, risk appetite, and budget process.
- Conducting complex risk analysis, to provide management with business insights, recommendations of strategies and business actions for profitable growth opportunities, consumer credit quality and behavior trends, desired risk/return relationships and portfolio performance.
- Partnering with business units in making strategic choices and investment decisions.
- Communicating opportunities, financial and process trade-offs from advanced statistical methods to senior leaders.
- Utilizing graduate-level research and analytical skills to perform data extraction, sampling, and statistical analyses using logistic regression, multinomial regression, multivariate analysis, discriminant analysis, neural network, principal components analysis, time series analysis, panel data analysis and etc.
- Analyzing and interpret big data and its impact in both operational and financial areas following comprehensive risk principles and procedures.
- Generating listings and reports from SAS programs using MACROS, ODS and PROC REPORT/TABULATE and using Word, Excel and Power Point.
- Extracting data from the database using SAS/Access, SAS/SQL procedures and created SAS data sets.
- Extensive use of SAS Macros and procedures like Proc SQL, Transpose, Univariate, Means, Freq. Performed statistical analysis using One-Way ANOVA
- Using SAS Data Integration Studio to develop various jobs processes for extracting, cleansing, transforming, integrating, and loading data into Data marts and Data warehouse database
- Extensively involved in Oracle PL/SQL programming to create Triggers, database Packages Procedures/Functions etc. Creation of database objects like Tables, Views, and Synonyms etc.
- Developing new or modified SAS programs to load data from the source and create study specific datasets, which are used as source datasets for report generating programs.
- Producing SAS Graphical reports showing Trend Analysis charts for campaign.
- Extensively used Arrays in SAS Data Steps.
- Extensive use of SAS PROC SQL Pass through Facility and SAS/CONNECT to work with Oracle database.
- Extensive use of GRAPH for generating various graphs and charts for analyzing the product sales.
- Done Enhancements for the existing business reports like incorporating new business variables.
- Developed, modified, and generated Monthly Business Review (MBR) reports summarizing business activity.
Environment: Base SAS, SAS/Macros, SAS/Access, SAS/Connect, SAS/Stat, SAS/Graph, SAS/SQL, SAS/ODS, SAS/ETL, Informatica, DB2, Teradata), XML, IBM AIX, Unix Shell Scripting, WINSQL, Ultra editor, Oracle, DB2, SQL Server, Mainframe, DTS and Windows XP, SAS Enterprise Guide, SAS Enterprise Miner, JMP, Spotfire
Confidential, Pleasanton, CA
Sr.SAS Programmer Analyst
- Working on Forecast Studio, Financial Management studio, Data Integration Studio and experience in modeling performing cost analysis and developing new products, analyzing using Dashboard studio and Tableau Server
- Preparing new datasets and modified existing datasets using Set, Merge, Sort, Update, Formats and Functions and created Table and Listings for the same.
- Participating in the development of outcomes and process measures, including technical specifications, to enable population measurement, guideline implementation, and evaluation.
- Testing complex statistical SAS routines using macros, vendor software, and software written by self and others.
- Performing automated model scoring within database to improve performance and achieve faster time-to-result, reducing excessive data movement across servers and enhance productivity.
- Creating tables to integrate SAS Embedded Process and Teradata, Oracle and run scoring models.
- Extensively used BASE SAS, Macros, and SAS SQL for advanced programming and production support.
- Used UNIX commands (Find, grep, search, locate) to search FTP directories for failed jobs and created process to automate the failed jobs in production.
- Actively involved in system integration testing, unit testing, regression testing, performance testing and back testing.
- Attending technical meetings & daily scrum meeting and worked closely with senior Business Systems Analyst, Architects, DBA’s, and other team members to understand the issue, find the root cause and resolve the issues.
- Converting Excel tables and flat (text) files into SAS datasets for Ad-Hoc analysis.
- SAS Enterprise Guide was used to convert existing SAS programs to SAS stored processes using dynamic prompts and produce packaging and streaming outputs as required
- SAS Management console was used to create metadata libraries.
Environment: SAS/Base, SAS/Macros, SAS/Access, SAS/Stat, SAS/SQL, SAS/ODS, SAS/GRAPH, Shell Scripts, IP Switch MS Office, SAS Enterprise Guide, Windows, and UNIX, SharePoint
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