Full-Time Lead Decision Scientist

Monzo is hiring a remote Full-Time Lead Decision Scientist. The career level for this job opening is Senior Manager and is accepting UK based applicants remotely. Read complete job description before applying.

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Monzo

Job Title

Lead Decision Scientist

Posted

Career Level

Full-Time

Career Level

Senior Manager

Locations Accepted

UK

Job Details

The mission of Borrowing Decision Scientists is to improve the customer and business outcomes through better automated decisioning, using Machine Learning and Statistical modelling. We have a primary focus in credit risk modelling, with our expertise also applied to predict and optimise utilisation, pricing, collection and marketing.

You will be taking a hands-on technical leadership role among a small team of very experienced and self-sufficient Decision Scientists. With in-depth knowledge and experience in the credit industry, you’ll drive innovations by identifying new opportunities of data and ML applications, and delivering business values across multiple Borrowing products. You’ll have a close relationship with leaders across Credit Strategy, Model Validation, Products and Engineers, to drive and influence strategic decisions and product roadmaps. You’ll also have the opportunities to work with external data suppliers and industry peers, to push the innovation frontiers for the credit industry.

With excellent technical skills, you’ll also spearhead the continuous development of our toolings, methodologies, and processes, to empower the team build better models easier and faster. You’ll serve as the champion for the quality and efficiency of model development, and ensure safe and scalable growth of our model portfolio. You’ll also have plenty opportunities to work with other modelling teams across Monzo, to collaborate on the best practices and latest technologies.

Our technology stack

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

  • Google Cloud Platform for all of our analytics usages
    • BigQuery SQL and dbt for our data modelling and warehousing
    • PyData stack for model development and offline deployment
    • Google AI platform for cloud computing
  • AWS for backend infrastructure
    • Python for ML model microservices
    • Go lang for most other microservices

You should apply if:

  • You are result oriented and motivated by the impact on our customers and business
  • You thrive in a fast-paced environment and comfortable with frequent context switching
  • You enjoy both the strategic thinking and influence, as well as hands-on solving technical problems
  • You want to build trust and influence a diverse range of leaders and stakeholders
  • You like inspiring people around you, with innovative thinking and high standard execution

You must have:

  • Excellent technical skills in Python, SQL, and statistics
  • Extensive knowledge of the credit industry, including the products, data, typical ML applications, and related regulations
  • Hands-on experience across the lifecycle of credit risk models, including project scoping, data curation, model optimisation, performance analysis, deployment, monitoring, and diagnosis
  • Successful track record of managing complex projects, with cross-functional teams and senior stakeholders

Even better if you have:

  • Previous experience of handling relationships with data suppliers such as credit bureaus
  • Previous experience of managing data and model governance

The Interview Process:

Our interview process involves the following stages:

  • Recruiter Call
  • Take Home Task
  • 4x (virtual) face-to-face stages
    • Technical interview
    • Case study
    • Value & collaboration
    • Leadership

FAQs

What is the last date for applying to the job?

The deadline to apply for Full-Time Lead Decision Scientist at Monzo is 29th of August 2024 . We consider jobs older than one month to have expired.

Which countries are accepted for this remote job?

This job accepts [ UK ] applicants. .

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