At a Glance
- Tasks: Lead data science initiatives to combat fraud and enhance user security.
- Company: Join Wise, a global tech company revolutionising money management.
- Benefits: Flexible work environment, diverse team culture, and opportunities for growth.
- Other info: We value diverse backgrounds and encourage all passionate individuals to apply.
- Why this job: Make a real impact on millions by safeguarding their financial transactions.
- Qualifications: Experience in data science, machine learning, and fraud detection is essential.
The predicted salary is between 80000 - 100000 £ per year.
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.
We’re looking for a Lead Data Scientist to join our growing Trust & Safety Team in London. 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.
As a Lead Data Scientist in the Trust & Safety team, you will leverage your expertise in data science to innovate and deploy models that detect and prevent fraudulent activities. Your work will directly influence our ability to safeguard our platform against unauthorized access and enhance our overall security framework. You will collaborate closely with cross-functional teams, including engineering, product, and security operations.
Key Responsibilities- Lead the development and deployment of advanced machine learning models to detect, predict, and mitigate account takeover attempts.
- Analyze large volumes of data to identify trends, patterns, and anomalies associated with potential ATO and Send Scam threats.
- Design and implement experiments to evaluate the effectiveness of fraud detection systems and continuously improve their performance.
- Collaborate with security analysts and engineers to translate business and security requirements into actionable data insights and solutions.
- Develop robust data pipelines, algorithms, and tools to support real-time detection and response to ATO and Send Scam threats.
- Stay informed about the latest advancements in data science, machine learning, and fraud prevention techniques to ensure state-of-the-art capabilities in ATO and Send Scam.
- Mentor and guide junior data scientists, fostering a culture of collaboration and continuous learning within the team.
- Proven experience in a data science role with a focus on fraud detection, cybersecurity, or fintech related domains.
- Have built machine learning models for Send Scam (Victim Identification) and Account Takeover (ATO).
- 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, unsupervised learning methods, deep learning, and graph-based solutions.
- 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 fraudulent activities.
- Solid knowledge of Python, ability to make and justify design decisions in code; familiarity with Git and code review; comfortable reading Java code and collaborating with engineering on services.
- Experience mining event logs to identify patterns and associations.
- 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 presentation skills to drive insight into action.
- Strong product mindset and ability to work independently in cross-functional and cross-team environments.
- Strong communication skills, able 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. 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. 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.
Lead Data Scientist - Trust and Safety employer: hackajob
Wise is an exceptional employer, offering a dynamic work culture in the heart of London where innovation meets inclusivity. As a Lead Data Scientist in the Trust & Safety team, you will not only have the opportunity to make a significant impact on our mission to safeguard millions of customers but also benefit from a collaborative environment that fosters continuous learning and professional growth. With a commitment to diversity and equity, Wise ensures that every employee feels valued and empowered to contribute to our shared goals.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Scientist - Trust and Safety
✨Tip Number 1
Network like a pro! Reach out to current employees at Wise on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for the interview by brushing up on your data science skills. Be ready to discuss your experience with fraud detection and machine learning models. We want to see how you think and solve problems!
✨Tip Number 3
Show off your passion for Trust & Safety! Share examples of how you've tackled similar challenges in the past. This will help us see your commitment to protecting users and enhancing security.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re serious about joining our mission at Wise.
We think you need these skills to ace Lead Data Scientist - Trust and Safety
Some tips for your application 🫡
Show Your Passion:When writing your application, let your enthusiasm for data science and fraud prevention shine through. We want to see how your passion aligns with our mission at Wise to make money management easier for everyone.
Tailor Your Experience:Make sure to highlight your relevant experience in fraud detection and machine learning. We’re looking for specific examples of how you’ve tackled similar challenges in the past, so don’t hold back on the details!
Be Clear and Concise:While we love a good story, keep your application clear and to the point. Use straightforward language to explain your skills and experiences, especially when discussing complex technical concepts.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity in our Trust & Safety Team!
How to prepare for a job interview at hackajob
✨Know Your Data Science Stuff
Make sure you brush up on your machine learning models, especially those related to fraud detection and cybersecurity. Be ready to discuss specific projects where you've built models for Send Scam or Account Takeover, as this will show your direct relevance to the role.
✨Show Off Your Collaboration Skills
Since this role involves working closely with cross-functional teams, prepare examples of how you've successfully collaborated with engineers, product managers, or security analysts in the past. Highlight your ability to communicate complex ideas to non-technical folks—this is key!
✨Stay Current with Trends
Keep yourself updated on the latest advancements in data science and fraud prevention techniques. During the interview, mention any recent trends or technologies you've been following and how they could apply to Wise's mission. This shows your passion and proactive mindset.
✨Prepare for Problem-Solving Questions
Expect to tackle some problem-solving scenarios during the interview. Practice articulating your thought process when faced with a data-related challenge, and be ready to explain how you would refine problem statements and develop actionable solutions.