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Program Data Analyst


Job ID : 34786

Location : Iselin, NJ

Company Name : VISART

Job Type : Full-Time, Part-Time, Contract, Training

Industry : Information Technology

Salary : $106600 - $107700  per hour

No. of Positions : I have ongoing need to fill this role


Required Skills : Writing, communication, Domain knowledge..

Benefits : Medical Insurance, Dental Insurance, Vision Insurance, 401K, Life Insurance


Job Description :

Responsiblties:

  • Develop and enhance data practices for generating investigative leads through patterns and trends related to the operations, policies, programs, and practices of the NYPD.
  • Develop and implement data harvesting, data analytics and other strategies that optimize statistical efficiency and quality, and oversee the work of those conducting the analysis.
  • Acquire data from primary or secondary sources and maintain databases/data systems.
  • Develop quality assurance systems for data and manage processes to ensure data quality.
  • Perform complex statistical analyses of sample and aggregate data sets to identify patterns, trends, and systemic issues.
  • Work as an advisor on systemic and individual investigations into the practices of NYPD.
  • Develop new methods for collecting data, new database applications for archiving and retrieval of statistics, and maintenance of records.
  • Develop error checking programs to determine if the data collected is reliable, timely, and valid.
  • Create and maintain databases, while preparing data sets for statistical analysis, including data cleaning and formatting.
  • Communicate clearly and effectively through compelling reports, presentations, and visualizations.
  • Conduct data related interviews connected to systemic and individual investigations.
  • Conduct policy assessments, memos and external correspondence.
  • Create data graphics.
  • Determine the preservation method of datasets and files related to the analytical work conducted for systemic and individual investigations.

Key Skills:

  • Data cleaning and preparation.
  • Data analysis and exploration.
  • Statistical knowledge.
  • Creating data visualizations.
  • Creating dashboards and reports.
  • Writing and communication.
  • Domain knowledge.

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