Our client is a global leader in Telecom Fraud Management.
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The client's winning aspiration is to empower every digital journey to be fearless, seamless, and fraud-free.We are looking for a Technical Product Manager (TPM) who can serve as the bridge between advanced engineering and real-world fraud management outcomes. The TPM will work at the intersection of technology and product strategy, driving the evolution of our platform from traditional rules-based and AIML capabilities
- a system that detects, investigates, and resolves fraud with minimal human intervention.KEY RESPONSIBILITIES:1.
Product Strategy & Roadmap - Define and own the technical roadmap for FMS, aligning with company strategy, Technology evolution and market trends. - Evaluate and prioritise product capabilities based on customer value and business impact. - Drive 0-to-1 feature development as well as the scaling and optimisation of product capabilities.2.
Technical Leadership & Cross-Functional Collaboration - Collaborate daily with Engineering, platform architects, and UX designers to translate product requirements into technical specifications. - Deeply understand product lifecycles - Lead technical discovery sessions, write detailed PRDs with acceptance criteria, and makeinformed trade-off decisions - Partner with architects to define a scalable, secure, and cloud-native solution.3.
Customer &Domain; Expertise - Develop deep expertise in telecom fraud typologies — bypass fraud, subscription fraud, roaming fraud, Wangiri, SIM swap, Robocalling, Spamming, Smishing and emerging attack vectors.



- Conduct regular customer interviews and advisory board sessions to understand evolving fraud patterns and operational pain points. - Translate customer needs into AI-powered product solutions that reduce false positives, accelerate investigation time, and improve fraud recovery rates.4.
Data-Driven Product Management - Define and track key product metrics - Use product analytics, A/B testing, and model performance dashboards to guide iteration and prioritisation. - Own revenue and adoption accountability for features within FMS.DESIRED CANDIDATE PROFILE: - Technical Credibility: Comfortable discussing model architectures, API designs, data pipelines, and system scalability with engineering teams — without needing to write the code. - Fraud Domain Expertise: Prior experience in fraud management, risk, or cybersecurity — preferably in telecom, fintech, or enterprise software — is strongly preferred. - Execution Excellence: Track record of driving products from concept to launch, owning metrics, and iterating based on data.
Not afraid to sign up for results. - Communication & Influence: Exceptional ability to synthesise complex technical and business concepts for diverse audiences — from C-suite to engineers to customers. - Customer Obsession: Relentless focus on understanding and solving real customer problems, backed by structured research and empathy.Required:



- Deep familiarity with fraud detection system architectures: real-time event streaming, rule engines, threshold management, case management, and reporting. - Understanding of telecom data structures — CDRs, signalling data (SS7, Diameter), network topology — and how they are used for fraud pattern identification. - Knowledge of fraud investigation workflows: evidence collection, case lifecycle management, escalation paths, and regulatory reporting requirements. - Awareness of key compliance and regulatory frameworks relevant to telecom fraud: GDPR, OFCOM, FCC, GSMA guidelines, and local CSP obligations. - Familiarity with integration patterns between FMS and adjacent systems: mediation platforms, BSS/OSS, network probes, and third-party threat intelligence feeds.Preferred / Bonus: - Experience working in or with AI coding environments (GitHub Copilot, Cursor, etc.) to accelerate product discovery. - Exposure to graph-based fraud detection, network analysis, or entity resolution systems. - Understanding of MLOps tooling (MLflow, Kubeflow, SageMaker) and model monitoring in production. - Experience with NLP for telecom data, CDR analysis, or voice/SMS fraud pattern recognition.EDUCATIONAL QUALIFICATIONS & EXPERIENCE: - Graduate / Post Graduate in Engineering (Computer Science, Data Science, or related field) from a premier institute. - Minimum 8–12 years of industry experience, with at least 4–5 years in a product management role. - Prior experience in telecom, fraud management, cybersecurity, or a data-intensive B2B SaaS environment is strongly preferred. xhfqzwm Disclaimer: Please ignore the salary range provided.

📌 Technical Product Manager - Fraud Management System (Madrid)
🏢 Mbr Partners
📍 Madrid