SUMMARY

• Around 7 years of experience working with R, Python, MySQL and Tableau as a Data Analyst/Data Science
• Proven expertise in employing techniques for Supervised and Unsupervised (Clustering, Classification, Decision Trees, KNN, SVM) learning, Predictive Analytics and Natural Language Processing (NLP).
• Experienced in advanced statistical analysis and predictive modeling in structured and unstructured data environment.
• Hands on experience of Data Science libraries in Python such as Pandas, NumPy, SciPy, Matplotlib, Seaborn.
• Hands on experience on R packages and libraries like ggplot2, Shiny, dplyr, reshape2, plotly, data.table, plyr, RMarkdown, ISLR, caTools etc.
• Expert in SAS programming, data processing, data collection, quantitative and qualitative data analysis and reporting.
• Experience in analysis, design, development, implementation and maintenance of complex quantitative models using SAS.
• Experience in extracting / creating, merging, analyzing and reporting large SAS datasets of up to 200 million records.
• Experience in developing and modifying SAS Programs and Macros for Data extraction, Data integration, Data cleaning, Validation, and Query writing and reporting.
• Experience working on BI visualization tools (Tableau, Shiny).
• Excellent understanding of Hadoop architecture and MapReduce concepts and HDFS Framework.
• Analytical, performance - focused, and detail-oriented professional, offering in-depth knowledge of data analysis and statistics; utilized complex SQL queries for data manipulation.
• Equipped with experience in utilizing statistical techniques which include Correlation, Hypotheses modeling, Inferential Statistics as well as data mining and modeling techniques using Linear and Logistic regression, clustering, decision trees, and k-mean clustering.
• Strong working experience in Extract/Transform/Load (ETL) design.
• Time Series Analysis (Seasonal ARIMA, Exponential Smoothing Models)
• Exceptional communication, team support, problem solving and analytical skills, abilityto learn and master new technologies efficiently.
• Experienced in writing Data Transformation and Data Cleansing rules for Data Mappingdocuments in Data Warehouse projects.
• Proven ability to lead and motivate people, possess excellent organizational, time management, communication and presentation skills.
• Received several awards and accolades in professional career, academics and extra-curricular activities.

TECHNICAL SKILLS

Programming: Python, R, SQL, HTML, C++

Databases: MySQL, Hadoop, SQL Server

Statistical Software: R, Python, Base SAS

ETL/BI Tools: Tableau, MS Excel, SQL

Statistical Methods: Time Series, regression models, intervals, principal splines, confidence component analysis and Dimensionality Reduction, bootstrapping

BI Tools: Microsoft Power BI, Tableau

Machine Learning Models: Linear Regression, Logistic Regression, Regularization, Support Vector Machines, Neural Networks, Decision Trees, Ensemble Methods like Random Forests.

PROFESSIONAL EXPERIENCE

Confidential, Nebraska

Data Analyst

Responsibilities:

• Utilized machine learning algorithms such as linear regression, multivariate regression, Naive Bayes, Random Forests, K-means, & KNN for data analysis.
• Used R ggplot2 and plotly packages to visualize and graphically analyses the data.
• Data pre-processing, splitting the identified data set into Training set and Test set.
• Performed data wrangling to clean, transform and reshape the data utilizing pandas library.
• Analyzed data using Sql, R, Python, Apache Spark and present analytical reports to management and technical teams.
• Data cleaning, Data wrangling, manipulation, and visualization. Extract data from relational databases and perform complex data manipulations. Also conducted extensive data checks to ensure data quality.
• Used R programming language to graphically analyses the data and perform data mining.
• Built and analyzed datasets using R and Python (in decreasing order of usage).
• Used R dplyr, plyr, data.table, lubridate, stringr packages to perform dataset manipulation.
• Used Data Quality validation techniques to validate Critical Data elements (CDE) and identified various anomalies.
• Extensively worked on statistical analysis tools and adept at writing code in Advanced Excel, R and Python.
• Analyzing Business requirements, data mapping requirement specifications and responsible for extracting data as per the business requirements.
• Involved in defining the Source To Target data mappings, Business rules, data definitions.
• Extensively used open source tools - R Studio(R) and Spyder(Python) for statistical analysis and building the machine learning.
• Generating weekly, monthly reports for various business users according to the business requirements.

Environment: R, Python, Data Quality, R Studio, Tableau, NumPy, SciPy, h2o, Pandas, SQL Server 2014, Matplotlib, Scikit-learn, HTML, XML, Shiny

Confidential, NE

Sr. DataAnalyst/ Machine Learning

Responsibilities:

• Design and develop machine-learning algorithms to address key business priorities like, Anti-money laundering, Fraudriskmanagement andCreditriskprediction.
• Diagnosed errors in a machine learning system and prioritized the most promising directions for reducing error.
• Applied satisficing and optimizing metrics to set up goal for ML projects.
• Applied linear regression, multiple regression, ordinary least square method, mean-variance, theory of large numbers, logistic regression, dummy variable, residuals, Poisson distribution, Bayes, Naive Bayes, fitting function, Deep networks etc. todatawith help of Scikit, Scipy, NumPy and Pandasmodule ofPython.
• Applied clustering algorithms i.e. Hierarchical, K-means with help of Scikit and Scipy and developed visualizations and dashboards using ggplot2,Tableau.
• R and Python scripting to wrangle and aggregate a war dataset consisting of 2+ million records and inconsistent formats.
• Developed largedatasets from structured and unstructureddata. Performdatamining.
• Tracked various campaigns, generating customer profiling analysis anddatamanipulation.
• ProvidedR/SQL programming, with detailed direction, in the execution ofdataanalysis that contributed to the final project deliverables. Responsible fordatamining.
• Analyzed large datasets to answer business questions by generating reports and outcome.
• Worked in a team of programmers anddataanalysts to develop insightful deliverables that supportdata- driven marketing strategies.
• Executed SQL queries fromR/Pythonon complex table configurations.
• Retrievingdatafrom database through SQL as per business requirements.
• Prepareddataframes by using Gsub () function inRfor identifying missingdatathat used for productiondataanalysis.
• Create, maintain, modify and optimize SQL Server databases and troubleshoot server problems.
• Manipulation ofDatausing R Programming.
• Datacollection, cleaned, filtered and transformeddatain the specified format.
• Prepared the workspace for Markdown.
• AccomplishedDataanalysis, statistical analysis, generated reports, listings, and graphs.
• Worked onRandPythonto identify business performance via Classification, tree map, and regression models along with visualizingdatafor interactive understanding and decision-making.

Environment:R,Python,Tableau, Logistic Regression, Boosted Trees, Hadoop.

SQL Expert

Confidential

Responsibilities:

• Work independently and collaboratively throughout the complete analytics project lifecycle including data extraction, preparation, and implemented machine learning techniques.
• Worked on different data formats such as JSON, XML and performed machine learning algorithms in R and Python.
• Hands on experience in implementing Naive Bayes and skilled in Random Forests, Decision Trees, Linear and Logistic Regression, SVM, Clustering, Principle Component Analysis.
• Worked on Text Analytics and Naive Bayes creating word clouds and retrieving data from social networking platforms.
• Developed R programs for manipulating the data reading from various Oracle data sources and consolidate them as single CSV File, and update the content in the database tables.
• Collected data from websites using API programming.
• Used text analytics through web scraping to understand customer sentiment feedback of marketing materials.
• Wrote complex SQL queries to include System Calendars, Inner Joins and Outer Joins to retrieve data from multiple tables.
• Designed easy to follow visualizations using Shiny, Tableau software and published dashboards on web and desktop platforms.
• Importing and exporting data from HDFS and SQL environment with R.
• Performed text mining to understand the financial behavior and preferences of potential customers.
• Worked with different types of Sources like XML files, DB Tables, Flat Files, and Destinations like DB Tables.

Environment: R - ggplot2, dplyr, Python's Pandas, NumPy, Sklearn, Seaborn, Machine Learning models, Matplotlib libraries, ISLR, Big Data Technologies (Hadoop, Hive, Sqoop, HBase, Map reduce), MS SQL Server.

Confidential . Queens, NY

Data Analyst

Responsibilities:

• Worked with several R packages likeggplot2, dplyr, plyr, data.tables, lubridate, reshape2, stringr, dbplyr, etc.
• Data Cleaning and Wrangling with R
• Image classification and finding accuracy with R
• Utilized statistical techniques to understand the data perform descriptive statistics (mean, median, mode, density distributions, box plots etc.), inferential statistics (t-test, ANOVA, Binomial Distribution etc.) and hypothesis testing.
• Created, analyzed and presented various performance parameters to better understand the nature of the data set using R.
• Used Correlation analysis to identify relation between variables, patterns, outliers and causal factors.
• Utilized statistical techniques to understand the data, perform descriptive statistics (mean, median,mode, density distributions, box plots etc.), inferential statistics (t-test, ANOVA, Chi square etc.) and hypothesis testing.
• Responsible for data aggregation, data pre-processing, missing value imputation and descriptive andinferential analysis.
• Leading business system design, testing, integration, implementation and support with principalresponsibility for overall functionality and project delivery.
• Created, analyzed and presented various performance parameters to better understand the nature ofthe data set using Tableau.
• Data elements validation using exploratory data analysis (univariate, bi-variate, multi-variateanalysis).
• Missing value treatment, outlier capping and anomalies treatment using statistical methods, derivingcustomized key metrics.
• Dummy variables where created for certain datasets to into the regression.
• Worked with several Python packages like Pandas, NumPy, Scikit-learn, Matplotlib, SciPy etc.
• Data Visualization extensively performed using TABLEAU .
• Used Tableau to refresh and make changes to the dashboards.

Environment: Python- Pandas, NumPy, Sklearn, Seaborn, Machine Learning models, R - ggplot2, dplyrMatplotlib libraries, Big Data Technologies (Hadoop, Hive, Map reduce), MS SQL Server

Confidential

SAS Analytics Consultant

Responsibilities:

• Maintained mainframes performance reports and created reports for online and batch applications for various servers. Created charts showing mainframe performance using SAS/GRAPH.
• Coordinated the production of monthly, quarterly, and annual performance reports for senior management.
• Modified data using SAS/BASE & Macros, performed statistical analysis of the data using SAS and prepared graphs using the modified data for business analysis.
• Created several of datasets on the Remote Server. Extracted data sets from mainframe server using PROC CIMPORT and created datasets in SAS libraries.
• Developed SAS programs with the use of SAS/BASE and SAS/Macros for ad hoc jobs.
• Executed SAS scripts on mainframes and the exported the output datasets into SAS.
• Maintained and enhanced existing SAS reporting programs for marketing campaigns.
• Executed reporting programs and download the results into EXCEL and built pivot tables for further analysis and presented the statistical reports for the marketing department.
• Moved data set across platforms (from PC and Mainframe to UNIX and Vice Versa).
• Involved in extracting, analyzing and auditing marketing data from the data-warehouse using SAS.
• Participated in marketing campaign-planning meetings with program managers in order to develop and document campaigns specifications.
• Created SAS data sets by extracting data from Oracle tables using SAS/CONNECT and SAS/ACCESS.
• Generated SAS/ MACROS and several PL/SQL stored procedures for reusability and to minimize data processing.
• Developed scripts, procedures and applications to generate sophisticated ad hoc reports using SAS/EIS and SAS/AF.
• Used PROC SQL for ad-hoc report programming, to perform the tasks like data manipulation of multiple views in Oracle, creation of the ad hoc reports for marketing research data, preplanning and doing ad hoc joining of multiple Oracle views.
• Wrote stored procedures for specific analytic reports.
• Wrote large aggregation SQL queries using in-line views.
• Ran SAS report programs and downloaded the results into Excel for data analysis.

Environment: SAS/BASE, SAS/STAT, SAS/MACROS, SAS/GRAPH, SAS/SQL, SAS/ODS SAS/CONNECT and SAS/ACCESS, SAS UNIVERSITY EDITIONS.