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Salary
≈ $9.5k – $23k per year (Estimated)
Location
In office (Metro Gate Indang)
Seniority
Junior · 1+ year exp

First seen by Alion on Sep 22, 2026.

Overview
Company
Impact
Profile match
Maya, formerly PayMaya, is a Philippine digital financial services company operating a wallet and a digital bank. It provides payments, savings, credit and merchant acquiring for consumers and businesses. The company is part of the PLDT affiliated Voyager Innovations group.

CORE PROFILE

Responsible for overseeing, administering, and maintaining Anti-Fraud-owned platforms and systems to ensure they support effective fraud monitoring, controls execution, and operational reliability. Serves as the main coordination point for Fraud Controls-related concerns housed in these platforms and systems, including issues or requests routed by Anti-Fraud Investigations teams for assessment, configuration support, and resolution follow-through.

NATURE OF WORK

  • Administer and oversee Anti-Fraud-owned platforms and systems to ensure fraud controls, workflows, access, and configurations remain aligned with Anti-Fraud operating requirements.
  • Serve as the coordination point for Fraud Controls-related concerns raised by Anti-Fraud Investigations teams, including triage, assessment, routing, tracking, and resolution follow-through.
  • Oversee operational tools used by Investigation teams, including those supported by SQL and Python, to help sustain accurate, controlled, and repeatable fraud operations processes.
  • Coordinate closely with Technology teams on system fixes, enhancements, releases, and enterprise infrastructure changes that may affect Anti-Fraud platforms, controls, or investigation workflows.
  • Support infrastructure and application change management activities by reviewing potential operational impact, validating fraud-control requirements, and ensuring appropriate stakeholder coordination before and after implementation.
  • Monitor platform behavior, job runs, alerts, and system outputs to identify issues, validate expected performance, and escalate anomalies that may affect fraud detection, prevention, or investigation support.
  • Maintain documentation of system configurations, operational procedures, change records, known issues, and resolution actions to support traceability, audit readiness, and knowledge transfer.
  • Identify opportunities to improve platform administration, script governance, issue management, and coordination processes as Anti-Fraud requirements, fraud patterns, and technology environments evolve.

DISPLAYED SKILL MASTERY

  • Regulatory, Control, and Fraud Domain Awareness: Apply sound understanding of fraud typologies, investigation workflows, control objectives, regulatory expectations, and governance requirements when supporting Anti-Fraud platforms and system changes.
  • Clear Communication and Stakeholder Facilitation: Communicate system issues, fraud-control concerns, change impacts, and recommended actions clearly to stakeholders within and outside Anti-Fraud; lead discussions, align next steps, and ensure concerns are tracked through resolution.
  • Fraud Systems and Technology Familiarity: Understand how fraud controls operate within Anti-Fraud-owned platforms, including how access, configurations, rules, releases, incidents, and infrastructure changes may affect fraud detection, prevention, and investigation support.
  • SQL, Python, and Basic Data Analysis: Review SQL- and Python-supported scripts, operational tools, job outputs, logs, alerts, and system data sufficiently to support issue validation, monitoring, impact assessment, and controlled coordination with Technology when needed.
  • Project, Change, and Work Management Tool Familiarity: Use Jira or similar tools to track incidents, defects, enhancements, change requests, dependencies, ownership, and resolution progress in coordination with Technology and other partner teams.
  • Cloud and Data Storage Familiarity: Demonstrate working familiarity with cloud-based storage and data-handling concepts, including AWS S3 buckets where applicable, to support access validation, file movement, issue investigation, and fraud-related data coordination.
  • Responsible AI Familiarity: Use AI tools efficiently for drafting, summarization, analysis, documentation, and workflow improvement while distinguishing tasks that can be AI-augmented and avoiding over-dependence for control decisions, sensitive assessments, or final validation.
  • Problem Solving, Documentation, and Sound Judgment: Assess system-related issues logically, maintain traceable records of configurations, changes, incidents, and decisions, and uphold confidentiality, integrity, and responsible decision-making in fraud-system operations.

REQUIRED QUALIFICATIONS

  • At least 1 year of experience in L1 systems support, technical support, application support, helpdesk operations, fraud operations support, or a similar operational technology support role.
  • Basic understanding of incident triage, ticket handling, issue escalation, production support, and service request management in an enterprise or technology-driven environment.
  • Working familiarity with Jira, ServiceNow, or similar ticketing/project management tools used to track incidents, defects, requests, ownership, status, and resolution progress.
  • Basic familiarity with SQL and Python, with the ability to review logs, job outputs, scripts, or simple queries used to support operational issue validation and coordination.
  • Basic understanding of application support concepts, user access administration, file handling, batch jobs, system alerts, and cloud-based storage such as AWS S3 buckets is preferred.
  • Exposure to financial services, banking, fintech, fraud operations, AML operations, risk operations, or other regulated technology environments is preferred.
  • Strong verbal and written communication skills, with the ability to explain system issues, document findings, provide status updates, and coordinate clearly with technical and non-technical stakeholders.

EDUCATIONAL BACKGROUND

  • BS or equivalent degree in Computer Science, Information Technology, Information Systems, Data Science, Computer Engineering, or other related technology fields; degrees in Mathematics, Statistics, or other quantitative disciplines may also be considered.
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