aipythonsqldata sciencefraud detectionmachine learningamltransaction monitoringexplainable ai
Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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У роли четкий senior-уровень в профильном AI-продукте для борьбы с финансовыми преступлениями, с заметным влиянием на клиентов и глубоким погружением в домен; при этом нужны серьезный опыт общения с клиентами и работы с production-системами.
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Высокий порог входаЧеткая зона ответственностиАктуальный стекAI для борьбы с преступностьюСобственный продукт
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Customer Data Scientist (AI): Tuning AML and fraud detection models against live customer transaction data with an accent on detection effectiveness, false-positive reduction, and regulatory defensibility. Focus on investigating alert quality and model drift, presenting findings to compliance and data science stakeholders, and validating production changes through backtesting and sample review.
Location: Hybrid in Munich or Berlin, Germany
Company
hirify.global provides AI-supported anti-money laundering and fraud detection technology combining traditional rules with explainable AI for banks and payment providers.
What you will do
Tune and optimize AML and fraud detection models and thresholds using customers’ live transaction data.
Investigate missed cases, alert quality, pattern drift, and detection performance, converting findings into tuning or configuration changes.
Analyze and communicate investigator productivity gains, false-positive cost reduction, and detection effectiveness improvements.
Present findings to customer risk, compliance, and data science stakeholders and defend model decisions.
Partner with Customer Value Partners on account strategy, value realization, and renewal-related improvements.
Document tuning decisions for regulatory defensibility and validate changes through backtesting, sample review, and formal sign-off.
Requirements
5–7 years of experience as a data scientist in a customer-facing role, including presenting analysis and defending model decisions directly to clients.
Required experience in AML, fraud detection, or financial crime analytics, including transaction monitoring, typologies, and false-positive impact.
Hands-on experience with Python, SQL, and production machine learning tooling.
Ability to act as the technical voice with customer risk, compliance, or data science stakeholders.
Experience translating model performance into actionable business value, including investigator hours saved, false-positive cost avoided, and cases caught.
Comfort working with ambiguity and live production systems rather than only offline research problems.
Ownership mentality and ability to proactively investigate detection-performance drift.
Nice to have
Experience in transaction monitoring or payments fraud detection at a bank, payment provider, or vendor serving them.
Familiarity with explainable AI and rules-based hybrid detection approaches.
Culture & Benefits
Hybrid work in Munich or Berlin.
Culture based on mutual trust, support, and professional growth.
Opportunity to contribute to the fight against money laundering, fraud, and terrorist financing.
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