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Data Analyst Resume

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Cleveland, OH

SUMMARY

  • Microsoft Data Science Certificated professional with 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 BI reporting 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.
  • 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 using R Studio.
  • Performed multiple Data Mining techniques 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.

PROFESSIONAL EXPERIENCE

Confidential, Cleveland, OH

Data Analyst

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 web 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.

Confidential, Boise, ID

Data Analyst

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- programming.
  • Used SPSS for data cleaning, reporting and developed efficient and modifiable statistical scenario.
  • 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

Data Analyst

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.
  • Responsible for gathering, preparing, analyzing, tracking, root cause analysis, & presenting data to solve complex inventory issues.
  • 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.

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