FP&A Intern: Automate AR, Build Dashboards & Insights

Socomec Group

Singapore

Vor Ort

SGD 48.000 - 72.000

Vollzeit

14 Tage+

Eine vollständige Bewerbung in einer Minute

Maßgeschneiderter Lebenslauf und Anschreiben – versandbereit.

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Zusammenfassung

Socomec Group is seeking a data-driven AR analyst to optimize credit risk reporting and automate AR workflows. You will analyze blocked orders, maintain credit rules, and develop dashboards to highlight at-risk accounts.

You will also manage SharePoint document control for 3rd-party invoices and liaise with Sales Admins and FP&A teams to present risk analyses and findings, identifying bottlenecks in AR processes.

Qualifikationen

  • Degree in Business, Accounting and/or equivalent.
  • Strong in data manipulation tools (Excel).
  • Is self-driven and disciplined.
  • Good interpersonal and communication ability.

Aufgaben

  • AR Report Optimization: Analyze and automate existing Accounts Receivable (AR) reporting workflows.
  • Credit Rule Maintenance: Review, update, and manage credit limit configurations.
  • Blocked Order Analysis: Evaluate held customer deliveries due to overdue balances or low credit.
  • Dashboard Development: Build clear, visual reports highlighting problematic accounts.
  • SharePoint Document Control: Set up and manage the archiving system for 3rd-party invoices.
  • Stakeholder Liaison: Present risk analyses and report findings to Sales Admins and FP&A teams.
  • Process Bottleneck Identification: Map current AR workflows to pinpoint manual inefficiencies.

Kenntnisse

Self-driven
Interpersonal communication

Ausbildung

Degree in Business/Accounting or equivalent

Tools

Excel

Jobbeschreibung

Socomec Group is seeking a data-driven AR analyst to optimize credit risk reporting and automate AR workflows. You will analyze blocked orders, maintain credit rules, and develop dashboards to highlight at-risk accounts.

You will also manage SharePoint document control for 3rd-party invoices and liaise with Sales Admins and FP&A teams to present risk analyses and findings, identifying bottlenecks in AR processes.

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