PROFESSIONAL SUMMARY:

• Microsoft Data Science d professional with about four plus years of experience in all phases of diverse technology projects specializing in Data Analysis, Data preparation and Data Visualization.
• Worked on analyzing large datasets on distributed databases and developing Machine Learning algorithms to gain operational insights.
• Experience with writing scripts for relational databases like Teradata, MYSQL, DB2, and Big data technologies like Hadoop - Hive to extract data for reporting and analysis.
• Expertise in Business Intelligence tools such as Tableau Dashboards Development and Server Administration, PowerBI.
• Performed preliminary data analysis using descriptive statistics and handled anomalies such as removing duplicates and imputing missing values using Talend prep tool.
• Experience in implementation of web analytics tools such as Heap, Adobe Analytics and marketing tools Confidential .
• Performed Dimensionality reduction using near zero variance and correlation techniques.
• Actively involved in Model selection, Statistical analysis using Gretl Statistical Tool.
• Validate the consolidated data and develop the model that best fits the data. Interpret data from multiple sources, consolidate it, and perform data cleansing.
• Performed multiple Data Mining techniques to track and derived new insights from the data.
• Proficient in implementing analytics & dashboards to enable enhanced business metrics performance with customer data through all digital channels.
• Ability to understand the data model, ETL, data warehouse and data flow between BI system components.
• Proficient in advanced Excel functions, pivot, graphs, VLOOKUP, HLOOKUP.
• Team player with good logical reasoning ability, coordination and able to complete projects independently.
• Experience in Agile development environment with Atlassian products such as Jira, Confluence.
• Team builder with excellent communications, time resource management and continuous client relationship development skills.

TECHNICAL EXPERTISE:

Tableau, PowerBI, Talend, GitHub, SAS, SQL, Teradata Studio, Db Visualizer, R, Azure Machine Learning, Microsoft Office, MS-Access, Teradata, DB2, MySQL, SQL Server, MongoDB, Hive, Hadoop.

PROFESSIONAL EXPERIENCE:

Data Analyst

Confidential, Cleveland, OH

Responsibilities:

• Conducted analysis that linked customer sentiment with user behavior and product usage data
• Developed calculations to measure NPS, Financial Confidence, and product usage
• Designed and automated interactive KPI dashboards with sentiment scores in Tableau
• Created interactive visualizations and dashboards using Tableau that enabled business users and executives to explore product usage and customer trends.
• Created custom SQL queries on various databases such as Teradata, MySQL, DB2 for data analysis and data validation.
• Performed data profiling and analysis on various datasets like customer profile data, branch hierarchy, contact history and email campaign data.
• Utilized Digital analytics data in extracting business insights and visualized the trends from the customer events tracked.
• Analyzed and developed reports using customer transactional data to create a multi - dimensional customer segmentation based on frequency of usage and product usage.
• Developed and maintained reports for both ad-hoc and ongoing business operating needs.
• Administered user groups, and scheduled instances for reports on large volumes of data in Tableau Server.
• Configured data extraction and scheduled incremental refreshes for data sources on Tableau server to improve performance of reports.
• Assisted in developing working documents to identify and get access permissions to database resources.
• Participated in grooming backlog, daily scrums, retrospectives and sprint reviews with product owner and technology partners to meet release timelines and adding business value.

Data Analyst

Confidential, Boise, ID

Responsibilities:

• Analyzed and reported client/customer data using large data sets like transactional and analytical data to meet business objectives.
• Responsible for all aspects of management, administration, and support of IBM's internal Linux/UNIX cloud - based infrastructure as the premier hosting provider.
• Worked with various databases like Oracle, SQL and performed the computations, log transformations, and Data exploration to identify the insights and conclusions from complex data using R.
• Used SPSS for data cleaning, reporting and developed efficient and modifiable statistical scenario.
• Extracted data from Oracle, SQL Server and DB2 using Talend to load it into a single data warehouse repository.
• Extensively used Star and Snowflake Schema methodologies.
• Experience on working different types of projects like migration projects, Ad-hoc reporting and exploratory research to guide predictive modelling.
• Applied concepts of R-squared, R.M.S.E, P-value, in the evaluation stage to extract interesting findings through comparisons.
• Proficient in the entire CRISP-DM life cycle and actively involved in all the phases of project life cycle including data acquisition, data cleaning, data engineering.
• Extensively used Azure Machine Learning to set up the experiments and creating Web services for the predictive analytics.
• Worked on writing complex SQL queries in performing Data analysis using window functions, joins, improving performance by creating partitioned tables.
• Prepared dashboards with drill down functions such as date filters, parameters, actions using Tableau to reflect the data behavior over time.

Confidential

Responsibilities:

• Designed, modeled, validated and tested statistical algorithms against various data sets including behavioral data and deployed predictive models using R - studio.
• Created interactive Dashboard using PowerBI for key Performance Indicators for business by connecting various data sources like Excel and SQL Database.
• Extracted patient data from Ambulatory and Inpatient Epic modules for ad-hoc and production reports.
• Performing tasks related to data reporting, including summarizing, documenting, validating, and creating charts.
• Performed Data Transformation method for Rescaling and Normalizing variables.
• Worked on data to increase cross-& up-sell revenues, enhance customer value or reduce non-credit losses.
• Contributed implementing models to identify, extract, summarize, and reduce or categorize the relevant qualitative financial input information like sentiment/feedback/news according to specific structures (templates) from a source text (digital news) to support decision making.
• Analyzed, transformed, and contextualized a variety of ingested data - social data, GIS data, POI& AOI data, and some consumer behavior data for building direct marketing predictive models.
• Responsible for working with stakeholders to troubleshoot issues, communicate to team members, leadership and stakeholders on findings to ensure models are well understood and optimized.
• Applied customer segmentation with Clustering algorithms and develop geo-demographic customer segmentation models.
• Delivered Interactive visualizations/dashboards using ggplot and Tableau to present analysis outcomes in terms of patterns, anomalies and predictions.