At a Glance
- Tasks: Develop and deploy advanced Machine Learning models to detect suspicious user behaviours.
- Company: Join Monzo, a fast-moving tech company with a focus on innovation.
- Benefits: Competitive salary, flexible working hours, £1,000 learning budget, and relocation support.
- Other info: Collaborative environment with opportunities for professional growth and knowledge sharing.
- Why this job: Make a real impact by ensuring customer safety through cutting-edge ML solutions.
- Qualifications: Experience in deploying ML models, strong Python and SQL skills, and a passion for innovation.
The predicted salary is between 86000 - 105000 € per year.
Cardiff, London or Remote UK | Salary £86,000-£105,000 + Incentive Awards tied to your performance + benefits
You'll play a key role by:
- This role sits as part of a multidisciplinary squad, collaborating with other Machine Learning Scientists, Data Scientists, Backend Engineers, Operations specialists, Product managers, and Risk managers.
- Leveraging your deep experience of developing and deploying advanced Machine Learning models to automatically and accurately detect suspicious user behaviours while minimising impact to genuine customers and operational costs.
- Adapting quickly and appropriately to changing fraud and financial crime trends, ensuring our detection systems remain performant through time.
- Designing machine learning solutions that scale globally.
- Justifying and demonstrating effectiveness along the way, ensuring the approach meets our business and customer needs.
You should apply if:
- What we’re doing here at Monzo excites you!
- You have a track record of deploying advanced Machine Learning models tackling real business problems with demonstrable impact, preferably in a fast moving tech company.
- You're impact driven and excited to own the end to end journey that starts with a business problem and ends with your solution having a measurable impact in production.
- You have a passion for sharing knowledge and raising the technical bar across the team.
- You have a self-starter mindset; you proactively identify the most impactful issues and opportunities and collaboratively tackle them without being told to do so.
- Using advanced ML techniques to ensure Monzo’s customers' money stays safe, even if their card, phone or account is compromised, sounds exciting to you.
- You have extensive experience writing production Python code and a strong command of SQL.
- You are comfortable using them every day, and keen to learn Go lang which is used in many of our backend microservices.
- You have experience developing and shipping deep learning, graph-based, and/or sequence-based ML architectures to production and delivering business impact.
- You thrive working on ambiguous problems and have a track record of helping your team and stakeholders resolve that ambiguity.
- You have strong communication skills and are able to explain complex technical concepts to non-technical stakeholders.
- You want to be involved in building a product that you and the people you know use every day, with a product mindset that prioritises customer outcomes and data-informed decisions.
- You're excited about fast-moving developments in Machine Learning and can communicate those ideas to colleagues who are not familiar with the domain.
- You’re adaptable, curious and enjoy learning new technologies and ideas.
Nice to haves:
- Experience in supporting your team in shaping the ML strategy of your area.
- Experience working with financial crime, operations and in regulated institutions.
- Commercial experience writing critical production code and working with microservices.
- Experience in evaluating ML models in live environments such as through A/B tests.
What’s in it for you:
- We’ll help you relocate to the UK.
- We can sponsor your visa.
- This role can be based in our London office, but we're open to distributed working within the UK (with ad hoc meetings in London).
- We offer flexible working hours and trust you to work enough hours to do your job well, and at times that suit you and your team.
- £1,000 learning budget each year to use on books, training courses and conferences.
- We will set you up to work from home; all employees are given Macbooks and for fully remote workers we will provide extra support for your work-from-home setup.
- Plus lots more! Read our full list of benefits.
Our interview process involves 3 main stages. We promise not to ask you any brain teasers or trick questions!
- 30 minute recruiter call
- 45 minute call with hiring manager
- 1 take home task
- 2 x 1-hour video calls with various team members
Our average process takes around 3-4 weeks but we will always work around your availability. You will have the chance to speak to our recruitment team at various points during your process but if you do have any specific questions ahead of this please contact us on tech-hiring@monzo.co
Senior Machine Learning Scientist in London employer: Referrals Only
At Monzo, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration among multidisciplinary teams. With a strong focus on employee growth, we provide a generous learning budget and flexible working hours, ensuring you can thrive in your role as a Senior Machine Learning Scientist while making a meaningful impact on our customers' financial safety. Whether based in our vibrant London office or working remotely across the UK, you'll enjoy a supportive environment that encourages experimentation and values your contributions.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Scientist in London
✨Tip Number 1
Network like a pro! Reach out to current employees on LinkedIn or other platforms. Ask them about their experiences and the company culture. This not only gives you insider info but also shows your genuine interest in the role.
✨Tip Number 2
Prepare for those interviews! Research common questions for Machine Learning roles and practice your answers. Make sure you can explain your past projects and how they’ve made an impact. We want to see your passion and expertise shine through!
✨Tip Number 3
Show off your skills! If you have any relevant projects, consider creating a portfolio or GitHub repository. This is a great way to demonstrate your technical abilities and problem-solving skills to potential employers.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re serious about joining our team at Monzo!
We think you need these skills to ace Senior Machine Learning Scientist in London
Some tips for your application 🫡
Show Your Passion:Let us see your excitement for the role! In your application, mention what specifically about our mission at Monzo resonates with you and how you can contribute to it. We love candidates who are genuinely interested in what we do.
Highlight Relevant Experience:Make sure to showcase your experience with deploying advanced Machine Learning models. Use specific examples that demonstrate your impact in previous roles, especially in fast-paced tech environments. We want to know how you've tackled real business problems!
Be Clear and Concise:When writing your application, clarity is key. Avoid jargon and keep your language straightforward. Remember, we want to understand your thought process and technical skills without getting lost in complex terminology.
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 the role. Plus, it shows you’re proactive and keen to join our team!
How to prepare for a job interview at Referrals Only
✨Know Your ML Models Inside Out
Make sure you can discuss your experience with deploying advanced Machine Learning models in detail. Be ready to explain how you've tackled real business problems and the measurable impact your solutions have had. This will show your depth of knowledge and ability to apply your skills effectively.
✨Communicate Clearly with Non-Techies
Since you'll be working with a multidisciplinary squad, practice explaining complex technical concepts in simple terms. Think about examples from your past where you successfully communicated with non-technical stakeholders. This will demonstrate your strong communication skills and your ability to collaborate effectively.
✨Show Your Passion for Innovation
Be prepared to discuss how you stay updated on fast-moving developments in Machine Learning. Share any personal projects or experiments you've undertaken that showcase your curiosity and willingness to innovate. This will highlight your self-starter mindset and enthusiasm for the field.
✨Prepare for the Take-Home Task
Since there's a take-home task involved, make sure you understand the expectations clearly. Review the job description and think about how you can align your solution with the company's goals. This is your chance to shine, so put in the effort to create something impactful that reflects your skills and understanding of the role.
