Technical Product Manager
Hace 4 días
España
MBR Partners
Jornada completa
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Our client is a global leader in Telecom Fraud Management.
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. Drive 0-to-1 feature development as well as the scaling and optimisation of product capabilities.
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.
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.
• Technical Credibility: Comfortable discussing model architectures, API designs, data pipelines, and system scalability with engineering teams — without needing to write the code.
• Prior experience in fraud management, risk, or cybersecurity — preferably in telecom, fintech, or enterprise software — is strongly preferred.
• Track record of driving products from concept to launch, owning metrics, and iterating based on data. 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.
• 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.) 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.
We are looking for a Technical Product Manager (TPM) who can serve as the bridge between advanced engineering and real-world fraud management outcomes. Drive 0-to-1 feature development as well as the scaling and optimisation of product capabilities.
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.
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.
• Technical Credibility: Comfortable discussing model architectures, API designs, data pipelines, and system scalability with engineering teams — without needing to write the code.
• Prior experience in fraud management, risk, or cybersecurity — preferably in telecom, fintech, or enterprise software — is strongly preferred.
• Track record of driving products from concept to launch, owning metrics, and iterating based on data. 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.
• 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.) 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.