SUMMARY

• 5 Years experiences served as a Data Scientist and Data Analyst. Expertise in using statistical tools: R, SAS, Python to perform Statistical Analysis, Data Mining, Machine Learning, Model Validation and Visualization. Familiar with big data platform like Hadoop, Spark. Profound experience in Finance and Online Retail Marketing industries. Possess an ability to understand business proposition and adapt quickly to deliver value to the team.
• Experience in using different relational database management systems like Oracle, TeraData, MS SQL, SQL Server, and MySQL.
• Proficient in R, SAS and Python, expertise on manipulating data, perform descriptive statistics, data validation and build predictive models.
• SAS BASE/ADVANCE certified programmer. Worked with SAS, SAS Enterprise Guide, SAS Enterprise Miner. Proficient in Base, SAS Macros, SAS Connect, SAS SQL and SAS ODS;
• Adept in advanced statistical analysis, machine learning, data mining and solving analytical problems using quantitative approaches, experience on Regression, Time Series, Classifier (Decision Tree, Random forest), Recommender Engine, Neural Network, clustering.
• Familiar with machine learning algorithm and statistical techniques like Decision Tree, Random Forest, Neural Network, Regression model, Time Series, Factor analysis, PCA (Principle component analysis), K - Mean Clustering, KNN (nearest neighborhood) clustering.
• Experience writing advance SQL programs for joining multiple tables, sorting data, creating SQL views
• Proficient in Tableau, designing and developing detailed reports and dashboard. Built interactive web applications for data analytics and visualization with Shiny R.
• Manipulating Large-scale data sets using big data techniques. Perform data analysis and statistical analysis on large scale data. Familiar with big data tools and platform: Hadoop, HDFS, Hive and map/reduce algorithms, Spark.
• PowerPoint, MS Excel (Filter, Freeze, Pivot tables, Functions, VLOOKUP, HLOOKUP), MS Visio, MS Project Management.
• Experience working on different operating systems (Unix, Windows, Mac) and have the ability to move data across various platform using FTP tools.
• Followed System Development Life Cycle (SDLC) methodology for the design, development. Followed CRISP-DM (Cross Industry Standard Process for data mining) methodology for data mining process.
• Worked with variety datasets from retails, finance, and digital industries.

TECHNICAL SKILLS

Skills: R: build predictive models, manipulate data, built interactive data visualization application, generate reports using R language and variety packages: dplyr, tydyr, reshape2, ggplot2, shiny, markdown, rhdfs, rhadoop, etc. SAS: SAS/BASE, SAS/SQL, SAS/MACRO, SAS/STAT, SAS/GRAPH, SAS Enterprise Miner; SAS Procedures Print, Frequency, Means, Summary, Tabulate, Chart, Gchart, Plot, Gplot, Univariate, Corr, Contents, Append, Datasets, Format, Sort, Transpose, Report, SQL, ANOVA, REG, Logistic, GLM, Macro, Import Export Python: manipulating data, and familiar with machine learning packages: scikit-learn, panda, nonpy. Microsoft Azure market, machine learning studio Shell scripting: Bash Apache Hadoop 2.0: Handling Big Datasets in Hadoop Distributed Framework. Hive: Querying using Hive Query Language, Hbase, pig Source control/version control: git Database: SQL Server, Microsoft Access, Oracle, Teradata Experience in operating systems: Windows, UNIX/Linux, Mac os. Microsoft word, excel, powerpoint, outlook, etc Tableau

PROFESSIONAL EXPERIENCE

Data Scientist

Confidential, NJ

Responsibilities:

• Built predictive models with advanced data mining techniques of machine learning algorithms include: Regression, Time Series, Neural Net work, classification models in R statistical computing environment.
• Performed ad hoc statistical, data mining, and statistical analysis on data collected from the market. Created ad­hoc reports and graphs as per the requirements of the business need using Tableau.
• Built supervised learning models on historical data to backtest different strategies and find the optimal strategy. Buit Time series models and visualized with Shiny R.
• Manipulated data by validating, cleansing and/or imputing errors, missing values and outliers, ensuring accuracy, completeness and consistency for analysis and reporting purpose.
• Using Tableau performed data visualization, created visualization dashboards, developed rich interactive graphics and data visualizations of large structured data in browser-friendly formats.
• Extracted/Transformed/Loaded the data from various data warehouses and sources like TeraData and SQL Server, Bloomberg depends on the requirement.
• Drew flowcharts indicating the input data sets, statistical techniques to get the required output and then writing the code.
• Interacted with other team members and lead to discuss the required developments to be made in coding to improve the functionality and effectiveness.
• Optimized analysis code to minimize processing time and required user intervention.
• Work closely with cross-functional teams to encourage statistical best practices with respect to experimental design and data analysis.

Data ANALYST

Confidential

Responsibilities:

• Using R, SAS and Python manipulated user behavior data such as search, browsing, and clicking, performed data analysis using clustering analysis, market research, and customer segmentation and profiling, for increasing response rate, click-through rate and profits
• Performed ad-hoc data analysis and visualization and deliver detailed report with Tableau.
• Using Hadoop and R built recommender engine based on collaborative filtering algorithms to provide recommender list, and worked with UI design team with website advertisement designing.
• Integrated big data from SQL Server and CRM data warehouse and marketing data marts based on specific business requests, while maintaining integrity and quality.
• Built machine learning models for text mining and word clouding.
• Worked with retail clients on understanding marketing initiatives objective, timeline, budgeting and channel and translating business requirements into technical solutions.
• Advised and support product decisions through insights, using quantitative and data mining skills to understand how user’s activity patterns.
• Communicated with production management to identify highly impact business areas, and implemented solutions into the production workflow.

Data Analyst

Confidential

Responsibilities:

• Performed daily data integrity checks & maintain security-level reference data. Responsible for troubleshooting and correcting information quality problems reported by end users, identified through the daily data integrity monitors.
• Performed testing and provide analysis of results that lead to the execution of requirements.
• Produced revenue, quantity, and historical trending reports for senior management on a monthly basis.
• Rapidly developed novel applications of classification, forecasting, simulation, optimization, and summarization techniques
• Applied quantitative analytical approaches to drawing conclusions and make recommendations to answer the business objective and drive the appropriate change. Translated recommendations into communication materials to effectively present to colleagues for peer review
• Created compelling interactive visualizations and presentations to enhance decision-making capabilities throughout the company
• Worked with rest of data engineering team to set analytic and product best practices.
• Using statistical knowledge constructed and evaluated A/B and multivariate tests. Understand and shared the root cause of changes the team makes to those KPIs. Communicated test results and findings to product and tech teams.