At a Glance
- Tasks: Transform customer service using advanced machine learning to enhance support experiences.
- Company: Join Monzo, a forward-thinking fintech revolutionising banking for everyone.
- Benefits: Competitive salary, flexible hours, learning budget, and relocation support.
- Other info: Diverse and inclusive workplace with excellent career growth opportunities.
- Why this job: Make a real impact on customer satisfaction while working with cutting-edge technology.
- Qualifications: Experience in machine learning, Python, and SQL; passion for solving real-world problems.
The predicted salary is between 115000 - 150000 £ per year.
We’re on a mission to make money work for everyone. We’re waving goodbye to the complicated and confusing ways of traditional banking. After starting as a prepaid card, our product offering has grown a lot in the last 10 years in the UK. As well as personal and business bank accounts, we offer joint accounts, accounts for 16-17 year olds, a free kids account and credit cards in the UK, with more exciting things to come beyond. Our UK customers can also save, invest and combine our pensions with us. With our hot coral cards and get-paid-early feature, combined with financial education on social media and our award winning customer service, we have a long history of creating magical moments for our customers! We’re not about selling products - we want to solve problems and change lives through Monzo.
About our Machine Learning Operations team: The challenges are significant: we aim to transform customer service by reducing the time and effort required to resolve issues, enhancing customer confidence and satisfaction. As part of Operations you’ll be at the forefront of our mission to provide unparalleled customer support experiences. Your role will be pivotal in leveraging state of the art machine learning techniques including LLMs to understand customer problems, to develop an effective human-in-the-loop system that augments automation with the efforts of support workforce (who we call COps) to more expediently and efficiently predict, identify, disambiguate and route customer problems at scale to support a rapidly expanding company with global ambitions across multiple geographies. You’ll be one of 4 ML engineers in Operations, embedded in product squads working alongside data scientists, backend, mobile and web engineers, product managers, user researchers, designers and operations specialists.
What you’ll be working on:
- Understand customers’ problems and support needs based on a variety of inputs.
- Route customers to the right COp who can support them and globally optimise those routing decisions across millions of customers and thousands of support staff.
- Automate the resolution of customers’ support needs through autonomous agents.
- Aid customer support in decision-making and pattern detection.
The technical approaches you take to solve these problems will be very much in your hands and we’ll strongly encourage and support experimentation and innovation. We’ll be expecting you to justify and demonstrate effectiveness along the way, making sure 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 executing on the development and deployment of advanced Machine Learning models tackling real business problems with demonstrable impact, preferably in a fast moving tech company. You have experience developing and shipping deep learning, graph-based, and/or sequence-based ML architectures to production and delivering business impact. 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. Using advanced machine learning techniques to directly improve customer support experiences and globally optimise routing and prioritisation across millions of customers and thousands of support staff 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 thrive working on ambiguous problems. 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 adaptable, curious and enjoy learning new technologies and ideas.
Nice to haves:
- Experience working with operations, financial crime and in regulated institutions.
- Commercial experience writing critical production code and working with microservices.
The interview process:
- 30 minute recruiter call
- 45 minute call with hiring manager
- 60 minute ML Modelling interview
- 60 minute Product & ML interview
- 60 minute behavioural interview
Our average process takes around 3-4 weeks but we will always work around your availability. You can also contact us at tech-hiring@monzo.com.
What’s in it for you:
- We can help you relocate to the UK.
- We can sponsor visas.
- 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, at times that suit you and your team.
- Learning budget of £1,000 a year for training courses and conferences.
- And much more, see our full list of benefits here.
- If you prefer to work part-time, we'll make this happen whenever we can - whether this is to help you meet other commitments or strike a great work-life balance.
Equal opportunities for everyone. Diversity and inclusion are a priority for us and we’re making sure we have lots of support for all of our people to grow at Monzo. At Monzo, we’re embracing diversity by fostering an inclusive environment for all people to do the best work of their lives with us. This is integral to our mission of making money work for everyone.
Senior Machine Learning Scientist, Customer Operations employer: Doist
Brink's is an exceptional employer that fosters a collaborative and innovative work culture, empowering employees to drive global commercial strategies in the ATM lifecycle solutions sector. With a strong focus on professional development and growth opportunities, employees are encouraged to expand their skills while contributing to sustainable growth and operational excellence. Located in a dynamic environment, Brink's offers unique advantages such as a diverse team and the chance to build long-term partnerships with global customers, making it a rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Scientist, Customer Operations
✨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 Doist!
✨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 Senior Machine Learning Scientist, Customer Operations at Doist.
✨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 Doist.
✨Apply Directly through Our Website
When you find a suitable opening like Senior Machine Learning Scientist, Customer Operations at Doist, 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 Senior Machine Learning Scientist, Customer Operations
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 Doist, 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 Doist. 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 Doist
✨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 Doist!
✨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.