{"id":1274971,"url":"https://alion.io/job/paynet-principal-data-engineer-fraud-projects","title":"Principal Data Engineer (Fraud Projects)","company":{"id":2112342,"name":"PayNet","domain":"paynet.my","url":"https://alion.io/company/paynet-my","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"BrioHR","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Malaysia"],"countries":["MY"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":21000,"max_usd":47000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":432},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"C#","optional":false},{"name":"GCP","optional":false},{"name":"Hadoop","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-09-26T01:11:32Z","employer_posted_date":"2026-09-26","last_verified_at":"2026-09-29T16:48:13Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"Why PayNet / Why Now\nShape data capabilities that strengthen how Malaysia’s payment ecosystem responds to fraud and scams\nBuild solutions spanning payment tracing, profiling, scoring, fraud-network analysis and emerging modus operandi\nWork at the intersection of data engineering, machine learning and industry-wide financial crime response\nPartner with banks, e-wallets, regulators and internal specialists on proofs of concept and ecosystem initiatives\nExplore new-generation technologies that uplift fraud, risk, compliance and security capabilities\nTL;DR\nOwn secure, reliable and usable data pipelines and infrastructure for analytics and data science\nProductionise statistical and machine learning models that improve fraud prevention and investigation outcomes\nDrive financial crime analytics, automation, monitoring and reporting across Risk & Compliance\nLead technical decisions with broad direction, clear accountability and independent delivery\nContribute at Senior or Principal level, bringing more than five years of relevant data science or engineering experience\nWhy This Role Matters\nTurn complex payment data into capabilities the ecosystem can use to combat fraud and scams\nBridge experimentation and production so analytical models deliver dependable operational value\nImprove collective fraud response by connecting data, systems and cross-industry stakeholders\nRaise the division’s ability to monitor, analyse and automate fraud, risk, compliance and CISO processes\nShape greenfield and cross-functional projects that strengthen PayNet’s services and security\nWhat You Will Actually Do\nBuild, maintain and continuously enhance data pipelines and infrastructure that keep data accessible, secure and usable\nProductionise machine learning and statistical models for payment tracing, profiling, scoring and fraud-network insights\nDevelop and test fraud solutions and microservices, including transaction scoring and centralised financial crime capabilities\nDrive analytical and automation initiatives across fraud, risk, compliance and CISO monitoring and reporting\nLead technical delivery across concurrent projects, deciding how to move from ambiguous requirements to robust outcomes\nEngage financial institutions, e-wallets, regulators, vendors and internal teams to shape practical ecosystem solutions\nExamples of This Role in Practice\nA fraud model performs well in experimentation; you decide how to engineer, deploy and monitor it for dependable production use\nPayment data sits across multiple sources; you shape a secure pipeline that makes it usable for tracing and network analysis\nBanks and e-wallets join an industry proof of concept; you translate shared needs into a testable data solution\nA new fraud pattern emerges; you build analysis that helps specialists discover accounts, identities and transactions of interest\nMonitoring relies on manual work; you drive automation that improves the quality and repeatability of risk reporting\nWhat Will Help You Succeed\nMore than five years of relevant experience in data engineering, data science or both, supported by a related degree\nStrong programming capability in Python and SQL, with working exposure to languages such as C#, VBA or equivalents\nHands-on experience with big-data technologies such as Hadoop or Spark, cloud platforms such as AWS, Azure or GCP, and container orchestration using Kubernetes\nApplied knowledge of machine learning, analytical scripting, databases, automation and data visualisation\nSound judgment, conceptual thinking and the confidence to take accountable technical decisions under broad direction\nClear communication and relationship skills across business users, financial institutions, regulators, vendors and technical teams","description_format":"text","description_chars":3741,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Financial Services"],"lifecycle":[{"event":"open","at":"2026-09-26T01:11:32Z"}],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.859,"p_room":1,"age_days":5,"expected_fill_days":24,"reasons":["conf:36","velocity","win:early"],"computed_at":"2026-10-01T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/paynet-principal-data-engineer-fraud-projects","json_url":"https://alion.io/job/paynet-principal-data-engineer-fraud-projects.json","meta":{"generated_at":"2026-10-01T10:45:02Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":1950,"day_limit":5000,"remaining_today":3050,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}