Business Intelligence Analyst

Employer: Pragmatic Play
Domain:
  • Others
  • Job type: full-time
    Job level: peste 5 years of experience
    Location:
  • BUCHAREST
  • Updated at: 01.08.2021
    Short company description

    Pragmatic Play is a leading content provider to the iGaming industry. Pragmatic Play offers a multi-product portfolio of innovative, regulated and mobile-focused gaming products.

    Our passion for premium entertainment is unrivalled. We strive to create the most engaging and evocative experience for all our customers across a range of products, including slots, live casino and bingo, all of which are available via a single API.

    Pragmatic Play’s Games Library contains unique in-house content consisting of over 100 proven HTML5 games, available in all currencies, 26 languages and all major certified markets. We release three new video slots every month, with plans in place to further expand this.

    Requirements

    • Advance degree (preferred)
    • 5+ years in an analytical position
    • Strong SQL, database and data structures knowledge;
    • Knowledge and experience working with Tableau;
    • Excellent analytical skills and forecasting abilities;
    • Strong problem-solving skills - ability to analyse available data;
    • Good communication skills - ability to communicate findings with management in a clear manner;
    • Knowledge of statistical analysis tools;
    • Both written and oral English skills.

    Responsibilities

    • Overall responsible for delivering reporting and analytics requirements of the business operation unites;
    • Lead on reporting, analytics and data exploration.
    • Utilize company data resources in order to generate accurate reports and dashboards.
    • Generate Weekly and Monthly reports in fast paste grow environment.
    • Design new data collection models in order to improve reporting and predictive operational performances.
    • Coordinate with relevant departments and agree SLA’s to complete projects and tasks.
    • Develop and introduce new data profiling and scoring models.
    • Build dashboards and reporting matrix to improve company needs.
    • Analyse data trends and highlight areas for improvement.
    • Help identify and built live alert systems.