Data Science Manager Financial Crime
@ Monzo Bank

Hybrid
£120,000
Hybrid
Full Time
Posted 21 days ago

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XXXXXXXXX XXXXXXXXXXXXX XXXXXXXXXX****** @monzo.com
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Job Details

Overview

At Monzo Bank, our mission is to make money work for everyone by simplifying banking. As a Data Science Manager Financial Crime, you will lead a dynamic team in a collaborative, agile environment to tackle financial crime issues through data-driven strategies, innovation, and real-time analytics.

About the Role

You will work closely with Product, Risk, and Engineering teams to improve financial crime detection, prevention, and mitigation. Your work focuses on:

  • Leading a team of data scientists and analysts.
  • Generating insights to shape financial crime strategies.
  • Driving data-informed product development.
  • Collaborating with cross-functional partners.
  • Ensuring robust data collection for insightful analytics.

Responsibilities

You will mentor team members, support their growth, manage stakeholder expectations across seniority levels and implement rigorous data strategies. You will use various tools from business intelligence to machine learning (Python, SQL) to lead impactful projects.

The Interview Process

The process involves a 30-minute recruiter call, a 45-minute call with the hiring manager, and three 1-hour video calls with team members, typically taking 3-4 weeks.

Benefits

  • UK relocation support and visa sponsorship available.
  • Flexible working hours and distributed working options.
  • Learning budget for training, books, and conferences.
  • Inclusive environment and equal opportunity employment.

Key skills/competency

  • data science
  • financial crime
  • analytics
  • leadership
  • strategic
  • machine learning
  • Python
  • SQL
  • stakeholder
  • agile
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How to Get Hired at Monzo Bank

🎯 Tips for Getting Hired

  • Research Monzo Bank's culture: Understand their mission and values deeply.
  • Customize your resume: Emphasize data science leadership and achievements.
  • Highlight relevant experience: Showcase financial crime and analytical projects.
  • Prepare for interviews: Practice answering scenario and technical questions.

📝 Interview Preparation Advice

Technical Preparation

Review Python coding challenges and SQL queries.
Study financial crime detection algorithms and ML techniques.
Practice Looker and real-time analytics scenarios.
Brush up on data integration and BI tools.

Behavioral Questions

Describe a conflict resolution in your team.
Explain a time you led a project change.
Share experience collaborating with senior stakeholders.
Discuss how you manage team growth challenges.

Frequently Asked Questions