Staff Data Scientist - Fraud
Staff Data Scientist - Fraud

Staff Data Scientist - Fraud

London Full-Time 43200 - 72000 £ / year (est.) No home office possible
Wise

At a Glance

  • Tasks: Lead the development of machine learning models to enhance fraud detection systems.
  • Company: Wise is a global tech company revolutionising how money is moved and managed.
  • Benefits: Enjoy a diverse, inclusive culture with opportunities for remote work and personal growth.
  • Why this job: Join a mission-driven team focused on innovation and making financial transactions safer for everyone.
  • Qualifications: 5+ years in AI systems, skilled in Python, and experienced in machine learning frameworks.
  • Other info: We value passion over qualifications; diverse backgrounds are encouraged to apply.

The predicted salary is between 43200 - 72000 £ per year.

  • Compensation: GBP 115,000 – GBP 150,000 – yearly

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.

The Fraud team at Wise is dedicated to safeguarding our platform against financial crime and ensuring the protection of our legitimate customers. Leveraging cutting-edge machine learning, real-time transaction monitoring, and data analysis, our team is responsible for developing and enhancing fraud detection systems. Software engineers, data analysts, and data scientists collaborate on a daily basis to continuously improve our systems and provide support to our fraud investigation team.

Our vision is:

  • Build a globally scalable fraud prevention and detection engine to maintain Wise as a secure environment for our legitimate customers.
  • Utilise machine learning techniques to identify potential risks associated with customer activity.
  • Foster a strong partnership between our fraud investigators and the product team to develop solutions that leverage the expertise of fraud prevention specialists.
  • Not only meet the requirements set by regulators and auditors but also surpass their expectations.

We are looking for a highly skilled Staff Data Scientist to lead technical innovation and drive the development of advanced data science solutions. This role is pivotal in enhancing our fraud detection capabilities and ensuring the security of our platform.

Here’s how you’ll be contributing:

  • Innovate and Develop: Lead the development and deployment of machine learning models, including neural networks, anomaly detection, graph-based models, Transformers.
  • Lead and Collaborate: Mentor team members and promote adoption of AI workflows for automation across the business. Collaborate with cross-functional teams to integrate data science solutions into Fraud prevention product offerings.
  • Deploy and Integrate: Develop scalable deployment strategies together with Platform teams and integrate LLMs with AI agents for seamless production use.
  • Optimise and Evaluate: Conduct large-scale training and hyper-parameter tuning, and define performance metrics to ensure high-quality model outputs.
  • Data Strategy and Management: Design and implement strategies for data collection, curation, and augmentation to support robust model training.
  • Documentation and Reporting: Communicate complex data findings to non-technical stakeholders effectively. Document the development and maintenance processes for models and features.

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 visitWise.Jobs .

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Staff Data Scientist - Fraud employer: Wise

Wise is an exceptional employer that fosters a collaborative and innovative work culture, particularly within the Fraud team where cutting-edge technology meets meaningful impact. Employees benefit from a diverse and inclusive environment that prioritises personal growth and professional development, alongside the opportunity to work with advanced machine learning techniques in a globally scalable setting. With a commitment to safeguarding customers and a mission to make money management easier for everyone, Wise offers a rewarding experience for those looking to make a difference.
Wise

Contact Detail:

Wise Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Staff Data Scientist - Fraud

✨Tip Number 1

Familiarise yourself with the latest trends in machine learning and fraud detection. Being well-versed in cutting-edge technologies like neural networks and anomaly detection will not only boost your confidence but also demonstrate your commitment to innovation during discussions.

✨Tip Number 2

Engage with the Wise community on platforms like LinkedIn and Instagram. By following their pages and participating in discussions, you can gain insights into their culture and values, which will help you align your approach when networking or interviewing.

✨Tip Number 3

Prepare to discuss your experience with data strategies and big-data frameworks. Be ready to share specific examples of how you've designed data collection and curation processes, as this is crucial for the role and will showcase your expertise.

✨Tip Number 4

Highlight your mentorship experience in previous roles. Since the position involves guiding and mentoring team members, sharing your past successes in fostering collaboration and innovation will make you a standout candidate.

We think you need these skills to ace Staff Data Scientist - Fraud

Machine Learning Expertise
Deep Learning Models
Neural Networks
Anomaly Detection
Graph-Based Models
Transformers
Python Programming
TensorFlow
PyTorch
AI Agent Frameworks
LLM Orchestration
MCP Usage
Data Strategy Design
Data Collection and Curation
Big Data Frameworks
Large Scale Databases
Technical Leadership
Mentorship Skills
Excellent Communication Skills
Cross-Functional Collaboration
Performance Metrics Definition
Hyper-Parameter Tuning

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experience in machine learning and fraud detection. Use specific examples of projects you've worked on that align with the responsibilities outlined in the job description.

Craft a Compelling Cover Letter: In your cover letter, express your passion for combating financial crime and how your skills can contribute to Wise's mission. Mention any experience you have with AI workflows and collaboration with cross-functional teams.

Showcase Technical Skills: Clearly list your technical proficiencies, especially in Python, TensorFlow, and PyTorch. Provide examples of how you've used these tools in previous roles to develop and deploy AI systems.

Prepare for Communication: Since excellent communication skills are essential, prepare to discuss complex data findings in a simple manner. Think of examples where you've successfully communicated technical concepts to non-technical stakeholders.

How to prepare for a job interview at Wise

✨Showcase Your Technical Skills

Be prepared to discuss your experience with machine learning frameworks like TensorFlow or PyTorch. Highlight specific projects where you've developed and deployed AI systems, especially in the fraud or risk domain.

✨Communicate Clearly

Practice explaining complex technical concepts in simple terms. Since you'll be communicating with both technical and non-technical stakeholders, being able to adapt your communication style is crucial.

✨Demonstrate Leadership and Collaboration

Share examples of how you've mentored team members or led projects. Emphasise your ability to collaborate with cross-functional teams, as this role requires working closely with software engineers and fraud investigators.

✨Prepare for Problem-Solving Questions

Expect to tackle real-world problems during the interview. Brush up on your problem-solving skills, particularly in relation to fraud detection and data strategy, and be ready to discuss your thought process.

Staff Data Scientist - Fraud
Wise
Location: London

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