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Monzo

Lead Machine Learning Scientist, FinCrime

Work from home

Remote role where the employee must remain based in a particular country.

United Kingdom only

Employer listed it 9 days ago ¡ Added 5 days ago

First listed 9 days ago and still open.

Salary

ÂŁ115,000 to ÂŁ150,000

Location

United Kingdom only

Timezone

GMT

Contract

Full-time

Experience

Lead

Category

Data

Stated by the employer in the job description

Remote flexibility

Work from home

This is a remote role, but the employee must be based in United Kingdom. It is work from home rather than work from anywhere.

What the employer says

  • Source listing states candidate location: "Cardiff, London or Remote (UK), UK"
  • Job description states: "based in our London office"

What Nomaders makes of it

  • Payroll and tax are likely handled in that country only

The quotes above are the employer's own words; the reading is ours. Always check the original listing and employment terms before working from another country.

About the role

🚀 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 their 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 ❤️

📍London/Cardiff/UK Remote | 💰 £115,000 - £150,000 + Incentive Awards tied to your performance + Benefits ✨

About our Machine Learning FinCrime Team:

Our Financial Crime Data team consists of over 25 people across 4 data specialisms: Analytics Engineers, Data Analysts, Machine Learning Scientists and Data Scientists. As a Lead Machine Learning Scientist, you’ll be working in a fast moving environment, building and iterating on our financial crime defensive capabilities to ensure we keep Monzo and our customers safe.

Our financial crime team has 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. We have a major influence on the overall customer experience and it’s our duty to keep our customers safe. The work we do results in directly measurable customer or company benefit, which is incredibly satisfying.

Our Machine Learning Scientists work on a range of problems within the different financial crime areas ranging from fraud detection and prevention, transaction monitoring for different types of suspicious activity through to customer risk assessment and operational tooling.

What you’ll be working on:

A Lead Machine Learning Scientist at Monzo is a technical Individual Contributor (IC) leadership position. As a technical Machine Learning expert, working with billions of rows of data stored on a modern cloud native data platform, we’ll be expecting you to leverage 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

Adapt quickly and appropriately to changing fraud and financial crime trends, 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.

Your day-to-day:

As a technical individual contributor, you’ll be providing technical leadership and shipping highly impactful ML-based solutions. You’ll be embedded in a cross functional product squad, working closely with product managers, data scientists, backend engineers and designers in an agile environment. You’ll also be a technical leader within the Machine Learning discipline, helping to steer technical work and drive up standards.

This will involve:

Working with stakeholders across the organization to identify and scope out the most impactful opportunities to tackle Financial Crime and Fraud with Machine Learning.

Leading the design and development of advanced real time Machine Learning models, for example exploring how neural network, graph-based, and sequence-based architectures can drive improvements in detection of financial crime.

Providing technical leadership to drive up levels of technical expertise and best practice across the Machine Learning discipline, leading by example and mentoring others.

Working closely with our MLOps team to steer the ongoing development of tools to enable rapid iteration of models and optimisations of the full ML model lifecycle.

You should apply if:

What we’re doing here at Monzo excites you!

Requirements

The employer hasn't listed requirements separately, they're described in the role summary above and on the original listing.

Benefits

  • ¡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
  • ¡#LI-REMOTE #LI-SR1
  • ¡Equal opportunities for everyone
  • ¡If you have a preferred name, please use it to apply. We don't need full or birth names at application stage 😊

How to apply

  1. 1Check the flexibility label above, work from home, matches where you plan to live and work.
  2. 2Tailor your CV to the role at Monzo, mentioning your remote working experience and working hours (GMT).
  3. 3Apply directly on the employer's careers page using the button below. Nomaders never handles your application.

Found 5d ago. Last checked 23 Sept. Always confirm the details on the original posting, salary and location can change after publication.

Listing sourced from Company boards.

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