TECHNICAL SKILLS:

Programming Languages: R, SAS(Base) D3, Python, C, C++, Java, J2EE (Servlets, JSP), XML, PHP, jQuery

Database skills: My - SQL, Microsoft SQL Server, Teradata, NoSQL, PL/SQL, T-SQL, Redshift

Analytics: SAS, SPSS, EXCEL, WEKA, SSIS(ETL), SSRS,SSAS

Scripting Languages: JavaScript, HTML, CSS and Python

Operating Systems: Windows, LINUX

Machine Learning Algorithm: Linear & Logistic Regression, Market Basket Analysis, Time Series, Apriori Algorithm, Na ve Bayes, Clustering, Principle Component Analysis, Factor Analysis, Decision Trees, Random Forests, Support vector Machines, Exploratory Data Analysis, ANOVA

Other tools: Tableau, Informatica, Microstrategy, SAS E-Miner, SAS Enterprise guide, R studio, Eclipse, MATLAB, Xilinx ISE simulator, MASM- Microsoft Macro Assembler, MS Office

PROFESSIONAL EXPERIENCE:

Analyst

Confidential

Responsibilities:

• Translate business and technology requirements into database design models
• Design and implement next generation of data warehouse systems
• Work closely with development, support, DBA and business teams
• Responsible for team level contributions to overall application development efforts within portfolio application(s)
• Experience with the processing, manipulation and analysis of large datasets.
• Experience with various supervised and unsupervised machine learning techniques, as well as peer grouping, clustering and classification using R .
• Experience with advanced concepts of MS Excel such as pivot tables, graphs and advanced functions VLOOKUP, IFELSE, etc. and Macros.
• Experience with data modeling, database design, complex SQL queries and query optimization
• Develops, enhances, tests, supports, maintains, and debugs implementations within business intelligence (BI) applications that support business continuity and problem incidence functions; competent to work under supervision on simpler visualization coding from documented logic.
• Experience with descriptive statistics and how to effectively represent them graphically using Tableau and Microstrategy.
• Worked under general direction on complex projects usually on specific assigned problems, receiving guidance and direction from more senior associates or manager, as needed.
• Awareness on business continuity and problem incident functions for which application is designed.
• Working knowledge of Waterfall and Agile development methodologies, Rally / CA Agile Central experience a plus
• Exercised good communication skills to work with service delivery and engagement partners.

Database-Graduate Assistant

Confidential, Charlotte

Responsibilities:

• Provide assistance to the professor for the course Database Design and Implementation
• Assisted professor with classroom instructions, exams, record keeping and projects
• Tutor and assist Under-grad and Grad students individually or in small groups to help them master assignments and to reinforce learning concepts presented by Professor for course - Database Design and Implementation- MySQL
• Perform weekly and monthly analysis using SSRS, Tableau to generate reports on merit level of students in different concepts of Database design, Normalization
• Maintain course Learning Management System(LMS) site, including but not limited to posting assignments, editing and posting notes and/or slide shows for student access, and entering grades as assigned
• Evaluate student performance, including grading exams, quizzes, assignments, and papers
• Meet with course instructor and assists in designing term project
• Maintain weekly office hours to communicate in person with students as needed
• Receive and promptly respond to student inquiries regarding grades, assignments, attendance, and course material

Junior Data Analyst

Confidential

Responsibilities:

• In the role of Data Analyst performed analysis and design of extensions to an existing data warehouse/mart business intelligence platform
• Analyzed large data sets using statistical software, such as SAS, R, Python, and SPSS, to discover new business insights
• Analyzed data in both application and reporting databases and solving the discrepancies
• Data cleaning, data visualization, detection of missing data and skewness, correlation analysis using heat maps, principal component analysis and model development were performed on the data
• Designed and built machine learning & statistical models and conducted analyses at the appropriate level of complexity to produce relevant results for the business
• Created complex SQL queries for validating target data against source data
• Modified the existing SQL queries according to the requests and executed them to check the performance
• Extensively used SQL programming in backend and front end Functions, Procedures, and Packages to implement business logics/rules
• Written Procedures and Functions using Dynamic SQL and written complex SQL queries using joins, sub queries and correlated sub queries
• Modelling using Logistic Regression for the binary response variable
• Random forest modelling was explored for better predictability
• Built model to predict binary response on dataset with 28variables. Achieved model accuracy of 75% and sensitivity of 54% with Random forest
• Developed Tableau visualizations and dashboards using Tableau Desktop

Data Analyst

Confidential

Responsibilities:

• Worked directly with the Business Data Architect into identifying customer’s interactions across systems and their correspondent data repository
• Provided customized and complex reports to client institutions and provide them with the analysis that informs their financial aid policies
• Analyze the data set and find the problem statement. Extracted, compiled and tracked data and analyzed data to generate reports
• Developed optimized data collection and qualifying procedure. Ensuring data integrity, updating and entering definitions
• Interpret data from primary and secondary sources using statistical technique and provide ongoing reports
• Translate data into understandable document by cleaning, transforming and visualizing
• Integrating data from multiples sources to build reporting spreadsheets and user interface which meet business information requirements
• Ensemble learning method applied for better predictive performance
• Worked with other team members to complete special project and achieve project deadlines
• Developing tidy dataset, Data visualization in R using dplyr, tidyr& ggplot2 packages.
• Develop prediction model using Linear/Logistic/Decision Tree/Random Forest models .
• Building Dashboard/Stories over data using SSRS, Tableau and Excel .
• Run reports based on team needs by writing SQL quires to extract data