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.
Reads like a Data Engineer role: pipelines and data infrastructure.
Tallinn, Estonia
Live, first seen by us 4 hours 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 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
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.
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.
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.
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.
59 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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.
- 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
Complete your application on jobs.smartrecruiters.com. The employer’s form will show what is required.
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New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
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.
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.
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.
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:
This role will give you the opportunity to:
Good to have
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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Tallinn, Estonia
Working pattern and location restrictions need checking in the full posting.
No clear work-authorization passage found. Eligibility is unconfirmed.