Senior Machine Learning Engineer

Key Skills

A/B Testing, Finance, GoLang, Google BigQuery, Jupyter Notebook, Machine learning techniques

Job Description

About us: 

We’re here to make money work for everyone and we're doing things differently. For too long, banking has been obtuse, complex and opaque.

We want to change that and build a bank with everyone, for everyone. Our amazing community suggests features, test the app and give us constant feedback so we can build something everyone loves.

We're focused on solving problems, rather than selling financial products. We want to make the world a better place and change people's lives through Monzo.

About our Machine Learning, Financial Crime Team:

As a Machine Learning Scientist, you’ll be working in an ever changing environment where we are building and iterating on our financial crime defence capabilities to ensure we keep Monzo and our customers safe. As a financial crime team we have a large impact on Monzo’s bottom line as fraud and scams are usually some of the largest cost line items in a bank's P&L. In addition, we have a great influence on the overall customer experience and it’s our duty to keep them safe. Most of the work we do results in directly measurable customer or company benefit which is incredibly satisfying.

Our Machine Learning Scientists don’t have a permanent assignment to a problem space and might rotate into different financial crime areas after some time. The major problem spaces that we are working in are: fraud detection and prevention, transaction monitoring for different types of suspicious activity, customer risk assessment and operational tooling to name the biggest ones. At the moment we are about 21 people in financial crime data, including Analytics Engineers, Data Analysts, Machine Learning Scientist and Data Scientists. 

What you’ll be working on:

As part of your job you’ll work closely with product managers, data scientists, backend engineers, designers and researchers in an agile product environment. You’ll champion the use of data and machine learning techniques, bring ideas to life through rigorous experimentation and A/B testing.

As a technical Machine Learning expert, working with large volumes of data stored on a modern cloud native data platform, we’ll be expecting you to leverage your skills and experience to help us to develop, deploy and maintain advanced Machine Learning solutions that enable us to: 

• Quickly detect emerging trends in fraud and financial crime
• Automatically and accurately detect suspicious customer behaviours
• Adapt quickly and appropriately to changes in customer and fraudster behaviours, ensuring our detection systems remain performant through time. 

The technical approaches you take to help 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. 

Our culture is open and focused on collaboration between different functions and individuals. It is fast paced and innovative where we try to push the boundaries of the current financial industry best practices. We put a lot of emphasis on feedback (up, side and downwards) and personal growth and development. 

Your day-to-day 

You’ll be a member of the machine learning discipline, working within a product squad in financial crime to help to design, build, analyse, and experiment with machine learning systems that make use of the data we gather.

We organise our machine learning projects into three distinct phases; you'll spend your time doing all three:

• Explore. We use BigQuery and Jupyter Notebooks to analyse data and design machine learning models for offline evaluation. For example, we are investigating machine learning powered assistants for our customer operations team, classifiers to detect financial fraud or to assess customer risk at signup.
• Launch. We build Python micro services and cron jobs to put promising machine learning models into production. We are actively working on automating as much of this step as possible: our goal is for any data scientist or ML engineer to be able to deploy a promising new model to production in less than a day.
• Iterate. We run A/B tests in partnership with other teams and analyse the results. Based on outcomes, we may decide to roll the model out to every customer or to explore improvements to the model for further testing.

You should apply if:

What we’re doing here at Monzo excites you!

• 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 self-starter mindset; you proactively identify issues and opportunities and tackle them without being told to do so
• Reducing financial crime and protecting customers with data driven strategies sounds exciting to you
• You have a solid grounding in SQL and Python, are comfortable using them every day, and keen to learn Go lang which is used in many of our microservices 
• You have multiple years of experience using advanced machine learning techniques to tackle real business problems preferably in a fast moving tech company
• You are comfortable exploring potentially ambiguous business problems within a complex and rapidly growing organisation.