SUMMARY

• Around 8+ Years of extensive IT experience wif 5+ years of experience as a Data Scientist/Analyst and 3 years of experience as IT Operations Analyst.
• Applied Forward Elimination and Backward Elimination for data sets to identify most statically significant variables for Data analysis.
• Experience working in Data Requirement analysis for transforming data according to business requirements.
• Utilized Label Encoders and One - Hot Encoder in Python to create dummy variables for geographic locations to identify their impact on pre-acquisition and post acquisitions by using 2 sample paired t test.
• Worked wif ETL SQL Server Integration Services (SSIS) for data investigation and mapping to extract data and applied fast parsing and enhanced efficiency.
• Developed Data Science content involving Data Manipulation and Visualization, Web Scraping, Machine Learning, Python programming, SQL, GIT and ETL for Data Extraction.
• Built Analytical systems, data structures, gather and manipulate data, using statistical techniques.
• Designing suite of Interactive dashboards, which provided an opportunity to scale and measure the statistics of the HR dept. which was not possible earlier and schedule and publish reports.
• Provided and created data presentation to reduce biases and telling true story of people by pulling millions of rows of data using SQL and performed Exploratory Data Analysis.
• Applied breadth of noledge in programming (R, Python), Descriptive, Inferential, and Experimental Design statistics, advanced mathematics, and database functionality (SQL, Hadoop).
• Migrated data from Heterogeneous Data Sources and legacy system (DB2, Access, Excel) to centralized SQL Server databases using SQL Server Integration Services (SSIS).
• Applied Descriptive statistics and Inferential Statistics on varies data attributes using SPSS to draw insights of data regarding providing products and services for patients.
• Developed and utilized various machine learning algorithms such as Logistic Regression, Decision trees, Neural Network models, Hybrid recommendation model and NLP for data analysis.
• Utilized data reduction techniques such as Factor analysis to identify most correlated values to underlying factors of the data and categorized the variable according to factors.
• Handled importing data from various data sources, performed transformations using Hive, Map Reduce, and loaded data into HDFS by using HQL queries in Hadoop.
• Performance Tuning: Analyze the requirements and fine tune the stored procedures/queries to improve the performance of the application.
• Developed various Tableau9.4 Data Models by extracting and using the data from various sources files, DB2, Excel, Flat Files and Big data.
• Interaction wif Business Analyst, SMEs and other Data Architects to understand Business needs and functionality for various project solutions.

TECHNICAL SKILLS

Programming Languages: SQL, R, and C/C++, C#.

Scripting Languages: Python, Powershell, VB Scripting.

Data Visualization: Tableau, IBM Cognos, Spotfire, IBM Watson, SAS VA, MS Excel.

Statistical Modelling: R Language and SPSS

Predictive Modelling/ Machine Learning Algorithms Tools: KNIME, Python

Prescriptive Modelling: Excel Solver.

Marketing Analytics: Google Analytics, Google Ad words, Mark Strat, Social Media Analytics, Keyword Analysis (SEO)

Development Platforms: Idle (Python GUI), Oracle SQL Developer, RStudio, MS-Office Packages.

Techniques: Data Visualization, Predictive Modelling, Statistical Modeling, Data Mining, Machine Learning, Text Mining, Sentimental Analytics, Business Intelligence, Linear Programming, Digital Marketing

Operating Systems: Windows XP/10/8.1/7/Vista, Unix, Linux.

Servers: Windows 2008 and 2012.

Databases: Oracle 10g/11g.

PROFESSIONAL EXPERIENCE

Data Scientist/Analyst Lead

Confidential, Boston, MA

Responsibilities:

• Lead a healthcare project in data analytics, ensuring high-quality work and standards using Agile Scrum Methodologies. Manage projects wif a focus on project planning, project tracking, team management, implementation, and reporting.
• Coordinates and integrates the team and individual efforts and builds positive professional relationships wif all internal and external clients. Organized and participated in the Sprint Planning, Sprint Review, and Daily Scrum meetings on a timely basis and attend conference calls wif senior leadership to keep them updated.
• Worked as a Data Scientist Lead to analyze both structured and non-structured data to create predictive models to perform data mining, text mining, and sentimental analysis of data.
• Expertise in writing SQL queries to fetch and prepare the data before modeling using best Data wrangling and Data profiling techniques such dat Data TEMPhas been cleaned, imputed, transformed, and validated.
• Used Python language to perform the statistical analysis, visualization, and forecasting of data as per the client’s requirement. Created functions using Python to be reused during coding along wif the best error handling techniques.
• Created statistical and predictive models like Logistic regression, Linear regression, ARIMA model, Bayes Classifier Algorithm, Artificial Neural Networks, Deep Learning, KNN, K-means clustering, Apriori Machine Algorithm, and Support Vector machine algorithm to perform supervised and unsupervised learning.
• Interpreted and analyzed data via descriptive Tableau to provide better insights about business problems.Created dashboards and identify KPI for measuring the business needs using Tableau.
• Worked on open source machine learning and analytics packages to generate deliverable modules and prototype demonstrations of their work.
• Programming wif Python and SQL.

Data Scientist/Analyst

Confidential, Herndon, VA

Responsibilities:

• Created views dat were published to internal team for review and further data analysis and customization using filters and actions.
• Created Heat Map showing current customers by color dat were broken into regions allowing business user to understand where we has most users vs. least users using Tableau.
• Projected and forecasted future growth in terms of number of customers in various classes by developing Area Maps to show details on which states were connected the most and publishing it on Tableau Server.
• Converted charts into Crosstabs for further underlying data analysis in MS Excel.
• Created Bullet graphs to determine profit generation by using measures and dimensions data from Oracle, SQL Server and excel.
• Blended data from multiple databases into one report by selecting primary key from each database for data validation.
• Combined views and reports into interactive dashboards in Tableau Desktop dat were presented to Business Users, Program Managers, and End Users.
• Developed story telling dashboards in Tableau Desktop and published them on to Tableau Server which allowed end users to understand the data on the fly wif the usage of quick filters for on demand needed information.
• Tested dashboards to ensure data was matching as per the business requirements and if their were any changes in underlying data.
• Rewrote various business process and tested result in MS Excel using various functions and sub query wif not exists.
• Involved in updating functional requirement document after development and created documentation for deployment team.
• Data quality check on variable level including missing values, unique values, frequency tables.
• Obtained the data from variety of sources such as Database, CSV, flat files etc.
• Wrote complex join SQL queries to extract, load data.

Environment: MS SQL Server for Data Analyst, MS Project, MS Visio

Data Scientist/Analyst

Confidential, NEW BRUNSWICK NJ

Responsibilities:

• This project was focused on customer clustering based on ML and statistical modeling effort including building predictive models and generate data products to support customer classification and segmentation.
• Develop a Estimation model for various product & services bundled offering to optimize and predict the gross margin
• Built sales model for various product and services bundled offering
• Developed predictive causal model using annual failure rate and standard cost basis for the new bundled services.
• Design and develop analytics, machine learning models, and visualizations dat drive performance and provide insights, from prototyping to production deployment and product recommendation and allocation planning.
• Worked wif sales and Marketing team for Partner and collaborate wif a cross-functional team to frame and answer important data questions. prototyping and experimenting ML algorithms and integrating into production system for different business needs.
• Application Machine Learning algorithms wif Spark Mlib standalone and R/Python.
• Worked on Multiple datasets containing 2billion values which are structured and unstructured data about web applications usage and online customer surveys
• Design, built and deployed a set of python modeling APIs for customer analytics, which integrate multiple machine learning techniques for various user behavior prediction and support multiple marketing segmentation programs
• Segmented the customers based on demographics using K-means Clustering
• Used classification techniques including Random Forest and Logistic Regression to quantify the likelihood of each user referring
• Designed and implemented end-to-end systems for Data Analytics and Automation, integrating custom visualization tools using R, Tableau, Power BI

Environment: MS SQL Server, R/R studio, Python, Spark frame work, Redshift, MS Excel, Tableau, T-SQL, ETL, RNN, LSTM MS Access, XML, MS office, Outlook.

Data Scientist lead/Analyst

Confidential

Responsibilities:

• Manage and lead a healthcare project in a data analytics field ensuring the high-quality work and standards using Agile Scrum Methodologies.
• Manage projects wif a focus on project planning, project tracking, team management, implementation, and reporting.
• Involved in creating an initial project scope, schedule, and budget wif risk assessment at various stages of the project.
• Coordinates and integrates the team and individual efforts and builds positive professional relationships wif all internal and external clients. Organized and participated in the Sprint Planning, Sprint Review, and Daily Scrum meetings on a timely basis and attend conference calls wif senior leadership to keep them updated.
• Worked as a Data Scientist Lead to analyze both structured and non-structured data to create predictive models and prescriptive analytics approach to do data mining, text mining, and sentimental analysis of data.
• Specialized in writing and running SQL queries to fetch and prepare the data before modeling using best data wrangling and Data profiling techniques such dat Data TEMPhas been cleaned, imputed, transformed, and validated.
• Work wif Data Scientists to identify key performance metrics and benchmarks related to user behavior and track them on a timely basis.Created dashboards and KPI for measuring the business needs using Tableau.
• Used big data technologies, ETL, statistics and causal inference, Deep Learning, Artificial Neural Networks, and linear programming to optimize the solutions
• Used Python language to perform the statistical analysis, visualization, and forecasting of data as per the client’s requirement. Created functions using Python to be reused during coding along wif the best error handling techniques.
• Created statistical and predictive models like Logistic regression, Linear regression, ARIMA model, Bayes Classifier Algorithm, Artificial Neural Networks, Deep Learning, KNN, K-means clustering, Apriori Machine Algorithm, and Support Vector machine algorithm to perform supervised and unsupervised learning.
• Interpreted and analyzed data via descriptive and predictive modeling tools such as Tableau, KNIME, and Spotfire to provide better insights about business problems.
• Worked on open source machine learning and analytics packages to generate deliverable modules and prototype demonstrations of their work.Perform large-scale data analysis and develop effective statistical models for segmentation, classification, optimization, time series, etc.
• Programming wif Python and SQL.

IT Operations Analyst

Confidential

Responsibilities:

• Worked as a Senior Data Analyst to analyze and interpret using data visualization tools and techniques, along wif the predictive and statistical modeling for the large banking data sets.
• Worked wif the real-time data sets related to financial data to interpret the results to solve the business problems and tracks the daily performance of the stocks.
• Schedule updates and send reports and KPI to the senior management on a timely basis. Involved in doing the Peer review of the work done by the team members so dat the quality of the deliverables is maintained.
• Wrote Python, VB Scripting, C and C# codes, and SQL codes to cater the client requirements.
• Interpreted and analyzed data via descriptive and predictive modeling tools such as Tableau, KNIME, and Spotfire to help the management in decision making.
• Wrote codes and scripts in R and Python language to visualize and predict the data as per the client’s requirement and prepare the datawif the help of SQL queries.
• Performing Extraction, Transformation, and Loading (ETL process) of the claim data sent by the clients/vendors in different file formats into ECP application using SQL queries and coding in Python. Ensuring dat the data is loaded accurately and completely. Work wif business users, customers, and the other ECP Analysts on the team to resolve issues dat may arise.
• Interacting wif the client and understanding the users’ requirements and functional specifications and providing resolution of the issues. Coordinating offshore - onsite communication.
• Key role in Project Management Operation (PMO) tasks from Project perspective, which involves creating project related business reports and sharing it wif the onsite (USA)-offshore (India) team members and business counterparts for the business and project analysis.