Product Manager - Telecom Fraud

Editx; Sint-Joost-ten-Node; On-site; EUR 90,000 - 130,000; Full time

Job summary

Editx is seeking a Senior Product Manager to own end-to-end fraud analytics products within the 365squared portfolio. You will engage senior customers and partners, translate market needs into commercially successful features, and set the strategic direction for the portfolio.

You will define and validate analytics definitions, lead AI/ML driven detection work, and work with engineering to deliver new voice anti-fraud capabilities.

Qualifications

• Senior product manager with deep telecom fraud expertise.
• Experience translating market needs into commercially viable products.
• Ability to engage senior customers and partners and set product direction.

Responsibilities

• Define product vision and roadmap for the fraud analytics portfolio.
• Lead AI/ML strategy for detection and analytics, ensuring explainability.
• Own end-to-end process to deliver new voice anti-fraud solutions and monetisation.
• Collaborate with engineering and external partners on call-treatment and integration.

Skills

Product strategy

Fraud analytics domain

AI/ML awareness

Stakeholder engagement

Roadmap planning

Job description

We’re now looking for a Senior Product Manager to join the 365squared team and take end-to-end ownership of key products across our fraud and data insights portfolio. This is an individual-contributor role for someone with deep telecom fraud expertise, strong product judgement and the confidence to set direction, engage senior customers and partners, and turn market needs into commercially successful products.

About the Role

You will own the full product lifecycle for 365squared's voice fraud analytics portfolio, commencing with a full refresh and upgrade of the current voice anti-fraud solution, and extending to future fraud and data monetisation solutions, including convergance to SMS and other communication channels. This includes translating deep domain expertise into deliverable analytics definitions (PRDs), building the commercial and go-to-market case, and enabling Sales and Operations to sell and support the product independently.

Key Responsibilities

1. Product Strategy & Vision

• Own the product vision and strategy for the fraud analytics portfolio, defining scope and differentiation based on detailed knowledge of operator pain points, competitor solutions and market trends.
• Define the product roadmap, prioritising features and new fraud use cases based on customer value, technical feasibility and commercial return.
• Act as the internal authority on the evolving global fraud landscape, proactively identifying new threat vectors (beyond current scope, e.g. new GSMA-classified fraud types) and building the case for their inclusion in the roadmap.
• Champion a customer and commercially focused product approach across the business.
• Own the AI/ML strategy for your portfolio, maintaining a current and high level understanding of how AI, including Gen-AI, Native-AI and LLMs, is being applied across fraud detection, analyst tools and customer-facing products. You will be tasked with applying your knowledge into a product roadmap with AI as a true differentiator.

2. New Product: Analytics & Technical Product Definition

• Own from ideation the end-to-end process to deliver a new voice anti-fraud solution to address current operator problems
• Produce complete, buildable analytics definitions for each in-scope fraud type, sufficiently detailed for Development to build against, including:
  • Fraud description, fraudster intent and operating model
  • Required data inputs and their relative weight per scenario
  • Detection approach, focused on advanced AI/ML-based detection engines to complement rule-based detection. The AI/ML solutions will span supervised and unsupervised machine learning, anomaly detection and behavioural analytics, with your expert input on which technique and engine fits which fraud type.
  • Design of the feedback loop between detection outcomes and model retraining, to ensure model performance, drift and explainability are actively managed in production.
  • Outputs, alerts, scoring and classification logic
  • Success metrics and targets
• Define call-treatment and mitigations in collaboration with Engineering and third-party voice firewall partners.
• Own the design for the shared analytics database and detection intelligence model that underpins current and future fraud modules, includin