Senior Product Analyst - Financial Crime

Description

The company is a global technology business that moves and manages money internationally, and this role sits in its Global Fraud Squad.

The Senior Product Analyst will help the company grow safely and efficiently by finding weaknesses in fraud controls and building fraud intelligence through analysis.

You will work with cross-functional teams to turn findings into action and improve detection, prevention and response to fraud.

Responsibilities

• Search proactively for anomalies, blind spots and control gaps using transaction, event and case data.
• Build rules and features for the detection engine to catch fraudsters.
• Share frequent findings and recommended actions with the squad so they lead to operational fixes.
• Run root-cause and cohort analyses to explain why controls succeed or fail, and propose prioritised fixes.
• Study how controls affect the customer experience and push for ongoing improvements.
• Work with Product Managers, Data Scientists, Operations and other Analysts to define and own fraud KPIs across products and markets.
• Identify, prioritise and drive initiatives with product managers.
• Connect business outcomes to control-level metrics and own performance for your team.
• Act as the main analytical contact for fraud workstreams on new market launches.
• Model pre-launch risk scenarios to estimate exposure and operational load.
• Give clear go/no-go recommendations that weigh risk, cost and customer impact.

Requirements

• Minimum 3 years of experience in product analytics in a complex, data-driven environment.
• A hustler mindset: you take work beyond analysis and get things done.
• Strong communication skills: you turn complex analysis into clear recommendations and influence senior stakeholders.
• A strong analytical mind and product intuition for payments, transaction flows and online behaviour.
• A proven record of digging into data, surfacing anomalies, reporting findings often and driving action across teams.
• Advanced SQL, Python (pandas/scikit or similar), and experience building dashboards in BI tools such as Looker, Tableau or PowerBI.
• Good to have: FinTech, payments or fraud experience.
• Good to have: experience with feature engineering and model monitoring.
• Good to have: familiarity with Airflow, DBT, Git, Snowflake and production data platforms.

Conditions

Equal opportunity: the company welcomes diverse teams and celebrates its international workforce.