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Senior Tableau Consultant Resume

SUMMARY

  • Around 10 Years of extensive IT experience as Data Analyst and 4 years of experience as Healthcare Data 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.
  • Designing suite of Interactive dashboards, which provided an opportunity to scale and measure the statistics of the dept. which was not possible earlier and schedule and publish reports using Data Visualization tools like Tableau.
  • Worked with 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 such as SAS.
  • 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 knowledge in programming (R, Python), Descriptive, Inferential, and Experimental Design statistics, advanced mathematics, and database functionality (SQL).
  • 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 SAS 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. Used Stored Procedures and Triggers in improve the performance of queries in PL/SQL
  • Developed various Tableau9.4 Data Models by extracting and using the data from various sources files, DB2, Excel, Flat Files and Big data.
  • Used ICD 10 to ensure that medical data relating to patient conditions, procedures and staff is properly maintained and up to date. Used ICD 10 to enable efficient and accurate billing, as well as effective measurement of the number of treatments and procedures that are being undertaken by one facility.
  • Interaction with Business Analyst, SMEs and other Data Architects to understand Business needs and functionality for various project solutions.

PROFESSIONAL EXPERIENCE

Senior Tableau Consultant

Confidential

Responsibilities:

  • Lead a healthcare project in data analytics, ensuring high - quality work and standards using Agile Scrum Methodologies. Manage projects with a focus on project planning, project tracking, team management, implementation, and reporting.
  • Expertise in dealing with structured and non-structured data to create predictive models to perform data mining, text mining, and sentimental analysis of data.
  • 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.
  • Using Filters in the reports of the Tableau to filter out data as per the granularity level. Created calculated fields in the reports for calculations.
  • Tested dashboards to ensure data was matching as per the business requirements and if there were any changes in underlying data using Tableau. Publish dashboards on Tableau server using Tableau Public.
  • Create various charts such as Tree maps, bar charts, histograms, line chart, maps to present the data in an interactive manner.
  • Perform forecasting and storytelling using Tableau Desktop.
  • Expertise in writing SQL queries to fetch and prepare the data before modeling using best Data wrangling and Data profiling techniques such that Data has been cleaned, imputed, transformed, and validated.
  • Making Use of the SQL functions such as Joins to merge data into a report coming from 3 billion records. Writing Stored Procedures and Triggers to perform certain task.
  • Using SQL to come with Data Modeling that represents logical modeling of the data using ERDs. Data quality check on variable level including missing values, unique values, frequency tables using SQL
  • Used SAS to do statistical analysis of data including hypothesis testing, Statistical parameters, simple linear regression and multiple linear regression, visualization of data, relationship between the independent variables and dependent variable.
  • Worked on Multiple datasets containing 3 billion values which are structured and unstructured data about web applications usage and online customer surveys.
  • 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.
  • Worked on open source machine learning and analytics packages to generate deliverable modules and prototype demonstrations of their work.
  • Used ICD 10 to ensure that medical data relating to patient conditions, procedures and staff is properly maintained and up to date. Used ICD 10 to enable efficient and accurate billing, as well as effective measurement of the number of treatments and procedures that are being undertaken by one facility.
  • Performed DRG reimbursement , data quality/accuracy, physician services and compliance audits.
  • Programming with SAS and SQL.

Senior Tableau Consultant

Confidential

Responsibilities:

  • Created views that 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 that were broken into regions allowing business user to understand where we have most users vs. least users using Spotfire.
  • 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 Server.
  • Converted charts into Crosstabs for further underlying data analysis in Tableau & Spotfire.
  • 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 using SQL Joins
  • Combined views and reports into interactive dashboards in Tableau Desktop that 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 with the usage of quick filters for on demand needed information.
  • Using Filters in the reports of the Tableau/Spotfire to filter out data as per the granularity level. Created calculated fields in the reports for calculations.
  • Tested dashboards to ensure data was matching as per the business requirements and if there were any changes in underlying data using Tableau.
  • Rewrote various business process and tested result in MS Excel using various functions and sub query with 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 using SQL.
  • 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

Tableau Consultant

Confidential

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 using SAS
  • Develop Estimation model for various product & services bundled offering to optimize and predict the gross margin
  • Used SQL queries to efficiently fetch the data out of the database by writing queries, nested queries, stored procedures, and triggers.
  • Using best data wrangling, profiling techniques to pre-process the data before putting into the model. Writing Advanced SQL queries using PL/SQL.
  • Using Data modeling techniques to define the logical model of the database. Making use of the SQL joins to get the data from various tables.
  • 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 that drive performance and provide insights, from prototyping to production deployment and product recommendation and allocation planning.
  • Worked with sales and Marketing team for Partner and collaborate with 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.
  • Used SAS to do statistical analysis of data including hypothesis testing, Statistical parameters, simple linear regression and multiple linear regression, visualization of data, relationship between the independent variables and dependent variable.
  • Worked on Multiple datasets containing 2billion values which are structured and unstructured data about web applications usage and online customer surveys. Dealing with ordinal data using SAS and perform the data mining.
  • Used SAS to perform both qualitative and quantitative analysis of the data sets to come up with mining of data.
  • Performed Data mining using SAS to check how many times each word is coming in the comment or the text messages.
  • Segmented the customers based on demographics using K-means Clustering
  • Used classification techniques including decision tree and Logistic Regression to quantify the likelihood of each user referring using SAS.
  • Designed and implemented end-to-end systems for Data Analytics and Automation, integrating custom visualization tools using R, Tableau & Spotfire. Created Dashboards using Tableau to tell the stories of the data sets.

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

Lead Data 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 with a focus on project planning, project tracking, team management, implementation, and reporting.
  • Involved in creating an initial project scope, schedule, and budget with risk assessment at various stages of the project.
  • Coordinates and integrates the team and individual efforts and builds positive professional relationships with 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 with senior leadership to keep them updated.
  • Worked as a Senior Data Analyst 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.
  • Perform data mining and analysis that impacts pricing and risk assumptions.
  • Create and review monthly/quarterly claims information and summarize for client reports using Tableau.
  • Specialized in writing and running SQL queries to fetch and prepare the data before modeling using best data wrangling and Data profiling techniques such that Data has been cleaned, imputed, transformed, and validated.
  • Work with 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 with 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. Created Statistical Models such as Linear Regression, Logistic Regression, ARIMA Model using SAS.
  • Interpreted and analyzed data via descriptive and predictive modeling tools such as Tableau & Spotfire, to provide better insights about business problems and do forecasting based on the historical data.
  • Worked on open source machine learning and analytics packages to generate deliverable modules and prototype demonstrations of their work. Performed large-scale data analysis and develop effective statistical models for segmentation, classification, optimization, time series, etc.
  • Programming with SQL & SAS.

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