At a Glance
- Tasks: Lead data science projects to combat fraud and enhance user security.
- Company: Join Wise, a global tech company revolutionising money management.
- Benefits: Flexible work environment, competitive salary, and opportunities for growth.
- Other info: Diverse team culture that values passion and innovative thinking.
- 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 60000 - 80000 £ per year.
hackajob is collaborating with Wise to connect them with exceptional professionals for this role.
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.
Qualifications
A bit about you:
- 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.
- 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 with mining into event logs to identify patterns and associations.
- 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.
Lead Data Scientist - Trust and Safety in Liverpool employer: Wise
Wise is an exceptional employer that prioritises the well-being and professional growth of its employees. With a dynamic work culture that fosters innovation and collaboration, team members are encouraged to develop their skills while contributing to meaningful resilience strategies on a global scale. Located in a vibrant city, Wise offers competitive benefits and unique opportunities for career advancement, making it an ideal place for those seeking a rewarding and impactful career.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Scientist - Trust and Safety in Liverpool
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Wise!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Lead Data Scientist - Trust and Safety at Wise.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Wise.
✨Apply Directly through Our Website
When you find a suitable opening like Lead Data Scientist - Trust and Safety at Wise, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Lead Data Scientist - Trust and Safety in Liverpool
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Wise, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Wise. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Wise
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Wise!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.