At a Glance
- Tasks: Lead the development of machine learning models to combat fraud and protect customers.
- Company: Join Wise, a leader in financial technology focused on security and innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on innovation and career advancement.
- Why this job: Make a real difference in preventing fraud while working with cutting-edge technology.
- Qualifications: Experience in deploying models, strong Python skills, and a collaborative mindset.
The predicted salary is between 80000 - 100000 € per year.
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
- 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 someone who will help maintain our existing machine learning algorithms, while helping to make them better and develop new intelligence to stop fraudsters.
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. Continuously monitor model performance and implement improvements based on feedback and testing.
- 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. Develop actionable intelligence and insights to inform the Fraud Risk Team’s strategies.
- Collaboration & Communication: Work closely with the Fraud Risk Team to understand business processes and risk factors. Communicate complex data findings and insights effectively to non-technical stakeholders.
- Risk Reduction Initiatives: Identify opportunities to reduce the impact of risks on good customers through data-driven strategies and interventions. Develop and test strategies to balance risk mitigation with customer satisfaction.
- Documentation & Reporting: Document the development and maintenance processes for models and features. Prepare and present detailed reports and dashboards that reflect risk assessment outcomes and model performance.
Qualifications
A bit about you:
- Proven track record of deploying models from scratch, including data preprocessing, feature engineering, model selection, evaluation, and monitoring.
- Strong Python knowledge.
- Ability to read through code, especially Java.
- Demonstrable experience collaborating with engineering on services.
- 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.
Some extra skills that are great (but not essential):
- Experience on working with non supervised algorithms.
- Prior experience in the fraud domain and a strong understanding of fraud detection techniques.
Lead Data Scientist - Fraud Prevention employer: Dangote Industries Limited
Wise is an exceptional employer that prioritises innovation and collaboration within its Fraud Risk Team, offering a dynamic work culture where data scientists can thrive. With a commitment to employee growth, Wise provides opportunities for professional development while working on cutting-edge machine learning projects that directly impact the security of our customers. Located in a vibrant tech hub, employees enjoy a supportive environment that fosters creativity and teamwork, making it an ideal place for those seeking meaningful and rewarding careers in fraud prevention.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Scientist - Fraud Prevention
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or even just grab a coffee with someone who works in fraud prevention. Building relationships can open doors that a CV just can't.
✨Show Off Your Skills
When you get the chance to chat with potential employers, don’t hold back! Share your past projects, especially those involving machine learning and data analysis. Let them see how you can bring value to their team.
✨Tailor Your Approach
Every company is different, so make sure you understand Wise's mission and values. When you’re in an interview, align your experiences with their goals in fraud prevention. It shows you’re not just looking for any job, but this job!
✨Apply Through Our Website
Don’t forget to apply directly through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at Wise.
We think you need these skills to ace Lead Data Scientist - Fraud Prevention
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Lead Data Scientist role. Highlight your experience with machine learning, model maintenance, and any relevant projects that showcase your skills in fraud prevention. We want to see how you can contribute to our mission!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about fraud prevention and how your background aligns with our goals at Wise. Be sure to mention specific experiences that demonstrate your problem-solving skills and collaboration with teams.
Showcase Your Technical Skills:Don’t forget to highlight your technical prowess! Mention your strong Python knowledge, experience with statistical analysis, and any familiarity with Java. We’re looking for someone who can dive into the nitty-gritty of data science, so let us know what you’ve got!
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to submit all your materials in one go. Plus, it shows us you’re serious about joining our team at StudySmarter!
How to prepare for a job interview at Dangote Industries Limited
✨Know Your Models Inside Out
Make sure you can discuss the machine learning models you've worked on in detail. Be prepared to explain your approach to model maintenance, optimisation, and how you've implemented improvements based on performance feedback.
✨Showcase Your Data Analysis Skills
Bring examples of your data analysis work to the interview. Highlight how you've identified trends and anomalies in data, and be ready to discuss how these insights have informed risk mitigation strategies in your previous roles.
✨Communicate Like a Pro
Practice explaining complex data findings in simple terms. Since you'll need to communicate with non-technical stakeholders, being able to convey your insights clearly will set you apart from other candidates.
✨Collaborate and Contribute
Demonstrate your experience working in cross-functional teams. Share specific examples of how you've collaborated with engineers or product teams to develop solutions that enhance fraud detection and prevention.
