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Lit Records Data Analyst Resume

EXPERIENCE:

Confidential

Lit Records Data Analyst

Responsibilities:

  • Maintain data integrity and cohesiveness across different databases included but not limited to NetCracker, MS Dynamics CRM, and OSPi using Excel
  • Support the team’s effort in keeping the databases updated following the company’s multiple acquisitions, crucial to the day - to-day operations Conduct NetCracker update test plans

Confidential

Graduate Admissions Assistant

Responsibilities:

  • Utilized PeopleSoft for applicants’ documents tracking and data entry Performed customer service activities i.e. responding to phone calls, helping walk-in students with application processes, using Salesforce to reply to prospect students’ emails

Confidential

Global Distribution Co-op

Responsibilities:

  • Updated and managed the company’s knowledge base of over 5000 responses with PMAPS
  • Utilized Salesforce to upload and update contact information with dataloader.io
  • Created five fact sheets and audited company’s information available in various consultant databases
  • Revamped distribution team’s information sharing hub with SharePoint Validated over 20 investment teams and professionals’ information for internal and external stakeholders use

Confidential

Sales Analytics Co-op

Responsibilities:

  • Conducted data pull for upper management decision making process, customers duns matching, weekly data imports, data validations using SQL Server
  • Developed new data import procedures to accommodate the migration from Oracle CRM to Salesforce and updated SQL Server 2005 to 2016 version by building a workflow using Alteryx

Confidential

Knowledge Base Analytics

Responsibilities:

  • Performed data cleaning, profiling on large dataset with RapidMiner and Excel, quantitative, qualitative analysis, article segregation, visualized statistics using Tableau and Excel by creating Dashboards
  • Offered multiple business process recommendations directly improve the company’s operation efficiency, audited and generated project reports for future use
  • Utilized R to perform data cleansing over 5 million records, combined from 2 data sets, of Confidential -listed properties
  • Performed quantitative and qualitative analysis of each attribute pertaining to Confidential a measure of error deviated from the Confidential 's estimated property sale price and actual price sold
  • Visualized areas of extreme Confidential

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