Alexander Fomin

Business Intelligence Manager

Moscow, Moscow City, Russia

About

Experienced professional with over 10 years of management of business analytics and intelligence, perfect combination of knowledge of relevant instruments and result orientation, efficiently supported by high level of interpersonal and communication skills. Strong experience in KPI dashboard development for project optimization and study of requirements and needs of business users. Excellence understanding of business weakness and strong experience to fix gaps and improve KPI’s performance.

Experience

  • Business intelligence and operational reporting manager at JTI
    Sep 2023 - Present · 2 yrs 11 mos

  • Business Intelligence Manager at AstraZeneca
    Nov 2022 - Aug 2023 · 10 mos

  • SFE business partner at STADA CIS
    Dec 2020 - Nov 2022 · 2 yrs

    Support field force structure (500+ empl.). Improve their efficiency throw HC optimization, new KPI integration and etc. Leading projects of optimization field force activities. Development new KPI's. Leading clients categorization processes. Development and Improving SFE dashboards. (SQL + Power BI). Working on improvement STI system for field force

  • Senior SFE analyst at Bayer
    Apr 2018 - Dec 2020 · 2 yrs 9 mos

    Created and managed doctor’s segmentation (SQL). Analysed of sales structure (300 empl.) model. Optimized structure. (SQL, Excel, Power Point). Prepared presentation and performed at cycle meetings and at global conference in 2020 with SFE part. Managed group’s database in SQL.

  • Philip Morris International (6 yrs 1 mo)
    • Sales information executive
      Aug 2015 - Mar 2018 · 2 yrs 8 mos

      Migrated reports from Excel to Tableau platform. (Microsoft SQL, VBA, DAX, Tableau). Created planning tools for field force in GT and KA channels. Developed KA offtake database for Moscow region

    • Trade marketing executive
      Mar 2012 - Aug 2015 · 3 yrs 6 mos

      Created forecasting model for distributors based on their sales history, market share and product price. Forecast data accuracy was ~90%.