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London, United Kingdom
Live, first seen by us 27 days agoWork setup in the employer’s posting: On-siteFrom the employer’s posting
Employment type in the employer’s posting: Full-timeFrom the employer’s posting
Hunt for anomalies, blind spots and control gaps in transaction and case data
Build rules and features for the fraud detection engine
Run root-cause and cohort analyses and propose prioritized fixes
Define and own fraud KPIs with PMs, data scientists and operations
Model pre-launch fraud risk and give go/no-go recommendations for new markets
Proactively hunt for anomalies, blind spots and gaps in controls using transaction, event and case data.
Build Rules and features for our detection engine to catch fraudsters.
Drive root-cause and cohort analyses to diagnose why controls succeed or fail and propose prioritized remediation.
Partner with Product Managers, Data Scientists, Operations and other Analysts to define and own fraud KPIs across Wise products and markets
Run pre-launch risk scenario modelling to estimate exposure and operational load. Provide clear go/no-go recommendations
Proven ability to dig into data, surface anomalies, communicate findings frequently, and drive actions across teams.
Experience with feature engineering and model monitoring.
Familiarity with Airflow/DBT/Git/Snowflake and production data platforms.
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Day 27
Similar jobs usually come down between day 5 and day 41.
From 10,658 similar postings that came down. Coming down is not always a hire.
49 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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- Proven ability to dig into data, surface anomalies, communicate findings frequently, and drive actions across teams. - Technical skills: advanced SQL, Python (pandas/scikit or similar), and experience building dashboards in BI tools (Looker/Tableau/PowerBI). Good to have
- Experience with feature engineering and model monitoring. - Familiarity with Airflow/DBT/Git/Snowflake and production data platforms. Additional Information
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We file this job under Analyst, by the work the posting describes.
Analysts answer business questions with data. They pull numbers with SQL, build reports and dashboards, and explain what changed and why to the people making decisions.
Most postings ask for SQL, spreadsheets, a dashboard tool such as Tableau or Power BI, and clear writing.
Unlike a data scientist, an analyst mostly explains what happened rather than building models that predict what will.
We’re looking for a Senior Product Analyst who is passionate about our mission of Money Without Borders to join our Global Fraud Squad. In this role, you’ll help Wise scale safely and efficiently by uncovering gaps in our fraud controls and strengthening our intelligence through analytics. You’ll work closely with cross-functional teams to turn insights into action, improving how we detect, prevent, and respond to fraud.
How you’ll contribute
Proactive detection & insights sharing
Proactively hunt for anomalies, blind spots and gaps in controls using transaction, event and case data.
Build Rules and features for our detection engine to catch fraudsters.
Deliver frequent findings and recommended actions to the squad that lead to operational fixes.
Drive root-cause and cohort analyses to diagnose why controls succeed or fail and propose prioritized remediation.
Understand customer experience due to our controls and drive continuous improvements.
Drive KPI Performance
Partner with Product Managers, Data Scientists, Operations and other Analysts to define and own fraud KPIs across Wise products and markets
Identify, prioritise and drive initiatives with our product managers
Link business outcomes to control-level metrics, define and own performance for your team
Analytical leadership in new market launches
Be the primary analytical contact for fraud workstreams on new market launches
Run pre-launch risk scenario modelling to estimate exposure and operational load.
Provide clear go/no-go recommendations that balance risk, cost and customer impact.
This role will give you the opportunity to:
Choose your path to impact – pick high-leverage problems, create the vision and own execution.
Grow as a Product & Fraud Analyst – develop deep fraud domain expertise and combine it with your analytical skills.
Work cross-functionally – partner with PMs, engineers, analysts, investigators, compliance and operations across markets.
Be highly visible – your analysis will regularly inform Product and Risk Committees and shape strategic decisions.
Deliver measurable change – your work will protect millions of customers while enabling Wise’s growth.
Ideally you'll have
Minimum 3 years experience in product analytics in a complex, data-driven environment.
Hustler-mentality. You can take work beyond the analysis and get things done.
Strong communicator – you translate complex analyses into clear recommendations and influence senior stakeholders.
Strong analytical mind and product intuition focused on payments, transaction flows and online behaviour.
Proven ability to dig into data, surface anomalies, communicate findings frequently, and drive actions across teams.
Technical skills: advanced SQL, Python (pandas/scikit or similar), and experience building dashboards in BI tools (Looker/Tableau/PowerBI).
Good to have
FinTech/payments and Fraud experience.
Experience with feature engineering and model monitoring.
Familiarity with Airflow/DBT/Git/Snowflake and production data platforms.
If you care about protecting customers and enabling growth through rigorous, product-focused fraud analytics and you like owning high-impact, high-visibility work, we’d love to hear from you.
For everyone, everywhere. We're people building money without borders — without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive.
We're proud to have a truly international team, and we celebrate our differences.
Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.
If you want to find out more about what it's like to work at Wise visit Wise.Jobs.
Keep up to date with life at Wise by following us on LinkedIn and Instagram.
Wise is a global technology company, building the best way to move and manage the world’s money.
Min fees. Max ease. Full speed.
Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money.
As part of our team, you will be helping us create an entirely new network for the world's money.
For everyone, everywhere.
More about our mission and what we offer.
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London, United Kingdom
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