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Decision Scientist Lead

🏢 Monzo 📍 London, England 💼 Company - Private
Currency:
£100,000 - £150,000
£8,333 - £12,500 / mo
Verified Corporate Employer (Authorized Corporate Employer)

This vacancy is published by an accredited employer with authorized corporate payroll and standard compliance adherence.

Transatlantic Cost of Living & Purchasing Power Benchmark

Verified Analytics
Location Base
London, England
Tier-1 UK Economic Zone
Est. Take-Home Pay
68% - 74% (After PAYE & NI)
Single tax filer baseline
Transatlantic Parity
1.0 GBP ≈ $1.28 USD Living Standard
Direct corporate benchmark

Position Overview & Specifications

London or Remote (UK) | £100,000 to £150,000 + Stock Options + Benefits

About Monzo:

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 the role:

The growth of Borrowing products is a key component of achieving Monzo's mission to make money work for everyone. This area is a top priority for Monzo as a business. The mission of Borrowing Decision Scientists is to improve the customer and business outcomes through better decisioning.

You will be taking a technical leadership role in our usage of machine learning models for automated decisions in the Borrowing Collective, with a primary focus in credit risk. You will apply your in-depth technical knowledge and experience in the credit industry to help the team develop best-in-class credit risk models, with innovations through novel data and technology. You will be responsible for delivering business values across multiple Borrowing products, with a close relationship with our Credit Strategy team, Model Validation team, Backend Engineers, and Product Managers. You will be able to influence our model and data governance practices, to help our business grow fast and safely.

You should apply if:

  • You are motivated by the impact on our customers and business, and thrive in a fast-paced environment.
  • You have extensive knowledge of the credit industry, including the products, various data sources, typical machine learning applications, and related regulations.
  • You have hands-on experience across the lifecycle of credit risk models, including project scoping, data curation, model optimisation, performance analysis, deployment, monitoring, and diagnosis.
  • You have solid technical skills in Python, SQL, and statistics.
  • You have a successful track record of managing complex projects, with cross-functional teams and senior stakeholders.
  • You know how to inspire people around you, with innovative thinking and high standard execution.

Even better if:

  • You have previous experience of handling relationships with credit bureaux.
  • You have previous experience of developing data and model governance procedures.

Our technology stack

We rely heavily on the following tools and technologies (note we do not expect applicants to have prior experience of all them):

  • Google Cloud Platform for all of our analytics infrastructure
  • dbt and BigQuery SQL for our data modelling and warehousing
  • Python for data science
  • Go to write our application code
  • AWS for most of our backend infrastructure

The Interview Process:

Our interview process involves the following stages:

  • Recruiter Call
  • Take Home Task
  • Final Stages (booking in parallel)
    • Technical interview
    • Case study
    • Value & collaboration
    • Leadership
  • Hiring Manager interview

Our average process for this level role takes around 5-6 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.com

What's in it for you:

£100,000 to £150,000 ➕ plus stock options & benefits

✈️ 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 books, training courses and conferences

➕ And much more, see our full list of benefits here

Equal Opportunity Statement

We are actively creating an equitable environment for every Monzonaut to thrive.

Diversity and inclusion are a priority for us and we are making sure we have lots of support for all of our people to grow at Monzo. At Monzo, embracing diversity in all of its forms and 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. You can read more in our blog, 2021 Diversity and Inclusion Report and 2022 Gender Pay Gap Report.

We're an equal opportunity employer. All applicants will be considered for employment without attention to age, ethnicity, religion, sex, sexual orientation, gender identity, family or parental status, national origin, or veteran, neurodiversity or disability status.

#LI-RP1 #LI-REMOTE

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Candidate Selection & Onboarding Process

1

Application & Resume Screening

Submit your tailored CV/Resume directly to the talent acquisition portal.

2

Technical & Competency Interviews

Virtual interviews with the hiring manager and multidisciplinary team.

3

Formal Offer & Benefits Negotiation

Written agreement outlining compensation, equity, retirement vesting, and relocation allowances.

4

Onboarding & Corporate Integration

Equipment provisioning, team orientation, and commencement of duties.

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Hiring Organization
Monzo

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Location: London, England
Eligibility: Verified Employer Direct Placement
Schedule: Company - Private
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