
Focused on global money transfers.
Senior Data Scientist - Financial Crime Risk at Wise
About the role
We’re looking for a Senior Data Scientist to join our growing Financial Crime Risk Team in Tallinn.
This role is a unique opportunity to work behind the scenes of company transactions, understand how we mitigate risk and at the same time provide our customers with the seamless service they deserve. What you build will have a direct impact on Wise’s mission and millions of our customers.risk and at the same time provide our customers with the
At Wise, we strive to create a world where money moves freely. Our dedicated Financial Crime Risk (Fincrime Risk) team plays a crucial role in safeguarding our customers and Wise from criminal activity. We are seeking a talented Senior Data Scientist to lead data-driven initiatives within the Fincrime domain and develop cutting-edge intelligence solutions.Risk (Fincrime Risk) team plays a crucial role in safeguarding our customers and Wise from criminal activity. We are
Role Overview: As a Senior Data Scientist on the Fincrime Risk team, you will leverage your expertise in data science to innovate and deploy models that enhance our Fincrime detection capabilities on a global level. Your work will directly influence our ability to safeguard our customers against criminal actors. You will collaborate closely with cross-functional teams, including engineering, product, and compliance.
Key Responsibilities:
- Lead the development and deployment of advanced machine learning models to enhance our detection of different criminal behaviours across different Wise markets.
- Analyze large volumes of data to identify trends, patterns, and anomalies associated with potential criminal behaviour.
- Design and implement experiments to evaluate the effectiveness of Fincrime detection systems and continuously improve their performance.
- Collaborate with analysts, compliance and engineers to translate business and compliance requirements into actionable data insights and solutions.
- Develop robust data pipelines, algorithms, and tools to support real-time detection and response to Fincrime activity.
- Stay informed about the latest advancements in data science and machine learning to ensure state-of-the-art capabilities in the Fincrime domain.
- Mentor and guide junior data scientists, fostering a culture of collaboration and continuous learning within the team.
A bit about you:
- Proven experience in a data science role, bonus if experience is related to fraud detection, anti-money laundering, or fintech related domains;
- Strong proficiency in machine learning frameworks and programming languages such as Python, R, or similar.
- Experience working with large datasets and data processing technologies (e.g., Hadoop, Spark, SQL).
- Familiarity with anomaly detection, supervised and unsupervised learning methods, and real-time data analysis.
- Demonstrated ability to work collaboratively in cross-functional teams and effectively communicate complex technical concepts to non-technical stakeholders.
- A proactive, problem-solving mindset with a passion for protecting users from criminal activities.
- You have a solid knowledge of Python, and are able to make and justify design decisions in your code. You know how to use Git to collaborate with others (e.g. opening Pull Requests on GitHub) and are able to review code. Ability to read through code, especially Java. Demonstrable experience collaborating with engineering on services;
- You have experience working with compliance in assuring effectiveness of controls;
- You are familiar with a range of model types, and know when and why to use gradient boosting, neural networks, regression, autoencoders, clustering or a blend of these;
- Experience with statistical analysis and good presentation skills to drive insight into action;
- A strong product mindset with the ability to work independently in a cross-functional and cross-team environment;
- Good communication skills and ability to get the point across to non-technical individuals;
- Strong problem solving skills with the ability to help refine problem statements and figure out how to solve them.
We’re people without borders — without judgement or prejudice, too. We want to work with the best people, no matter their background. So if you’re passionate about learning new things and keen to join our mission, you’ll fit right in.
Also, qualifications aren’t that important to us. If you’ve got great experience, and you’re great at articulating your thinking, we’d like to hear from you.
And because we believe that diverse teams build better products, we’d especially love to hear from you if you’re from an under-represented demographic.
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](https: //wise.jobs/our-mission) and
[what we offer](https: //wise.jobs/what-we-offer).
Required skills
Data science
Machine learning
Risk analytics
Statistical analysis
Model deployment
Cross-functional collaboration
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About Wise

Wise
PublicWISE inspires girls and women to study and build careers in science, technology, engineering and manufacturing.
1-50
Employees
Bradford
Headquarters
$8.0B
Valuation
Reviews
10 reviews
3.8
10 reviews
Work-life balance
3.2
Compensation
4.0
Culture
4.1
Career
3.5
Management
3.7
72%
Recommend to a friend
Pros
Flexible work hours and remote options
Supportive and approachable management
Collaborative environment and teamwork
Cons
High workload and unpredictable demands
Communication issues and lack of direction
Stressful and overwhelming work environment
Salary Ranges
117 data points
Junior/L3
Mid/L4
Senior/L5
Junior/L3 · Data Analyst
1 reports
$91,000
total per year
Base
$70,000
Stock
-
Bonus
-
$91,000
$91,000
Interview experience
4 interviews
Difficulty
2.3
/ 5
Duration
14-28 weeks
Offer rate
50%
Experience
Positive 25%
Neutral 25%
Negative 50%
Interview process
1
Application Review
2
Recruiter Screen
3
Online Interview Round
4
Technical/Role-specific Interview
5
Final Interview
6
Offer Decision
Common questions
Technical Knowledge
Past Experience
Behavioral/STAR
Role-specific Skills
Problem Solving
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