At a Glance
- Tasks: Develop and deploy advanced ML models to detect fraud and protect customers.
- Company: Join Monzo, a forward-thinking company focused on innovative financial solutions.
- Benefits: Enjoy competitive salary, flexible working, and opportunities for professional growth.
- Other info: Be part of a dynamic squad with a focus on innovation and measurable results.
- Why this job: Make a real impact by shaping scalable systems that protect users globally.
- Qualifications: Experience in machine learning, Python, SQL, and collaboration with diverse teams.
The predicted salary is between 70000 - 90000 £ per year.
Monzo is seeking a Machine Learning Scientist to join a multidisciplinary squad and deploy advanced ML models that detect fraud and protect customers.
You will own end-to-end work from business problem to production solution, shaping scalable, globally deployed systems.
You will write production Python, work with SQL and Go, collaborate with data scientists, engineers, and risk teams, and continuously justify approaches with measurable impact.
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Senior ML Scientist — Fraud-Detection & Scalable AI in London employer: EngineersOfAI
Graphcore is an exceptional employer, offering a dynamic work environment where innovation thrives and every team member can contribute to groundbreaking advancements in AI technology. With a strong focus on employee growth, Graphcore provides ample opportunities for professional development and collaboration with industry experts, all while being part of the prestigious SoftBank Group. Located in a vibrant tech hub, employees enjoy a culture that values creativity, inclusivity, and the chance to make a significant impact in the rapidly evolving field of artificial intelligence.
StudySmarter Expert Advice🤫
We think this is how you could land Senior ML Scientist — Fraud-Detection & Scalable AI in London
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We think you need these skills to ace Senior ML Scientist — Fraud-Detection & Scalable AI in London
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!
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Craft a Tailored Cover Letter:For a full-time role at EngineersOfAI, 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 EngineersOfAI. 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 EngineersOfAI
✨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!
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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
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✨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.
