Fraud Data Analyst

Selamat Datang di Situs Lowongan Kerja Indonesia Terbaru 2026 dan Saat ini kami ingin memberitahukan Info Terbaru Mengenai Informasi Loker dari Perusahaan Amar Bank dengan posisi Fraud Data Analyst. Untuk selengkapnya silahkan baca deskripsi lowongan kerja di bawah ini dengan seksama dan teliti, beserta persyaratan minimal lowongan kerja di yang telah tertera dan dijelaskan di bawah ini.

Amar Bank melalui program rekrutmennya saat ini sedang membuka lowongan kerja untuk posisi Fraud Data Analyst di Jawa yang bertujuan untuk meningkatkan kinerja operasional di dalam maupun luar kantor Amar Bank. Perusahaan Tersebut sedang mencari calon tenaga kerja yang siap diterjunkan ke setiap divisi bagian perusahaan yang sesuai dengan posisi, kemampuan dan keahlian para pencari kerja tersebut. Berikut ini adalah detail lengkap persyaratan untuk posisi Fraud Data Analyst di Jawa Perusahaan Amar Bank:

Key Responsibilities

• Data Instrumentation: Collaborate with Product and Engineering to define requirements for capturing fraud signals.
• Analysis & Detection: Identify anomalies, suspicious patterns, and credit fraud indicators like manipulated documents or synthetic identities.
• Investigation: Conduct deep dives into high-risk users and transactions to uncover new fraud typologies.
• Logic Implementation: Translate insights into fraud detection rules, monitoring systems, and risk models.

Requirements

• Years of Experience: Minimum of 5 years in fraud-related roles within Financial Services (Banking, Fintech, or Digital Lending).
• Education: Bachelor’s degree in Finance, Engineering, Data Science, Statistics, Computer Science, or a related field.
• Skills: Proficiency in identifying patterns and anomalies in behavioral and transactional data.
• Technical Knowledge: Understanding of fraud typologies (identity fraud, shell entities, document manipulation) and familiarity with querying/visualization tools.
• Collaboration: Ability to work across teams (Product, Risk, Engineering) and communicate recommendations clearly to stakeholders.

Bonus Point

• Experience in credit fraud or trust & safety analytics.
• Work history involving device data, behavioral signals, or real-time monitoring tools.
• Experience contributing to fraud models or scoring systems.