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Senior Product Analyst - AUP (Fraud Squad)

Reads like a Data Engineer role: pipelines and data infrastructure.

Pay
Pay not listed
Work setting
On-site — work setting source
Work setup in the employer’s posting: On-site
From the employer’s posting
Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting

What you’ll work on

Full posting
  • Hunt for anomalies and control gaps in transaction, event 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 across products and markets

  • Run pre-launch risk modelling and give go/no-go recommendations for new markets

From the employer’s posting
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.
define and own fraud KPIs across Wise products and markets
Run pre-launch risk scenario modelling to estimate exposure and operational load.

What you’ll bring

All qualifications

Core experience

  • 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.
Qualification wording
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.
Apply at Wise

Posting record

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Status in our records
Live
First seen by us
Nov 11, 2026today
Recorded sightings
1
Reposted
once since Oct 22, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.

How this job compares

Time since we first saw it

Day 0

Early. Similar jobs usually come down between day 6 and day 55.

At Wise, jobs usually come down by about day 11.

From 12,958 similar postings that came down, and 356 of Wise’s. Coming down is not always a hire.

Wise is hiring

59 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring at a steady pace
  • Takes jobs down quickly
  • 42% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • dbt
  • Looker
  • Power BI
  • Snowflake
  • Tableau
  • Airflow
  • pandas
  • scikit-learn
Where the posting names them
- 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

Your next step

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Demand for Data Engineer roles

New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.

Weekly new Data Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 834, the most 1,323, and the latest week had 1,323.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

Job Description

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.

Here's how you'll contribute to the team:

  • 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.

Qualifications

  • You've minimum 4 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.

Additional Information

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.

Company Description

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.

Source details

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Tallinn, Estonia

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