Lead Data Scientist - Fraud Prevention
Job Description
hackajob is collaborating with Wise to connect them with exceptional professionals for this role.
Scroll down the page to see all associated job requirements, and any responsibilities successful candidates can expect.
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.
Job Description
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.
Here's how you'll be contributing:
We are seeking a highly motivated Lead Data Scientist to join our Fraud Risk Team. In this role, you will level up the intelligence and maintain and refine existing models, develop new features, and create new intelligence to reduce the impact on good customers. You will work closely with the Fraud Risk Team to support the effective management and mitigation of risks associated with our receiving processes. Further you will help grow our data science team in space.
Key Responsibilities:
Model Maintenance and Improvement:
- Maintain and optimise existing risk models to ensure their accuracy and reliability.
Innovate and Develop:
- Lead the development and deployment of machine learning models, features and help deploy intelligence to production
Data Analysis & Intelligence Creation:
- Conduct thorough data analysis to identify trends, patterns, and anomalies that can aid in risk mitigation.
Collaboration & Communication:
- Work closely with the Fraud Risk Team to understand business processes and risk factors.
Risk Reduction Initiatives:
- Identify opportunities to reduce the impact of risks on good customers through data-driven strategies and interventions.
Documentation & Reporting:
- Document the development and maintenance processes for models and features.
Qualifications
A bit about you:
- Proven track record of deploying models from scratch, including data preprocessing, feature engineering, model selection, evaluation, and monitoring.
Some extra skills that are great (but not essential):
- Experience on working with non supervised algorithms
Additional Information
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. xxuwjjq
Keep up to date with life at Wise by following us on LinkedIn and Instagram.