Data Analyst - Fraud

Moniepoint

Greater London

On-site

GBP 55,000 - 75,000

Full time

14 days+

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Benefits offered by this job

Health insurance
Annual bonus
Learning & development

Job summary

Moniepoint is seeking a Data Analyst (Fraud) to investigate attacks, quantify impact, and translate findings into actionable mitigations across fraud operations and engineering.

You will build dashboards and reports to monitor fraud trends, work with data scientists and product managers, and proactively identify emerging patterns to flag risks before they escalate.

Qualifications

  • Proven data analyst experience in fraud or related field.
  • Advanced SQL: complex queries over large datasets.
  • Experience in fraud, risk, or financial services; understands mitigation trade-offs.
  • Proactive mindset with initiative to dig into anomalies.
  • Some exposure to Python or scripting for data manipulation.
  • Proficiency with a BI tool (PowerBI, Looker, Tableau, Superset, Redash).
  • Strong stakeholder management; able to influence decisions with data.
  • Comfort in fast-paced, cross-functional teams with shifting priorities.
  • Excellent written and verbal communication skills.
  • Bachelor’s degree in CS, Statistics, Math, Engineering, or related field.

Responsibilities

  • Investigate fraud attacks, quantify impact, and present findings that guide prioritisation and response.
  • Propose and refine rule-based mitigations, collaborating with fraud operations and engineering to implement.
  • Build and maintain reporting and dashboards to monitor fraud trends and key metrics.
  • Collaborate with fraud operations, data scientists, engineers, and product managers to translate insights into action.
  • Identify emerging patterns and flag risks before they escalate.

Skills

SQL
Fraud knowledge
Python basics
BI tools
Stakeholder mgmt
Communication
Cross-functional
Excel

Education

Bachelor's degree in CS/Statistics/Math/Engineering

Tools

PowerBI
Looker
Tableau
Superset
Redash
Git

Job description

Moniepoint is an all-in-one financial services platform for emerging markets and the second-fastest growing company in Africa.
Since 2019, Moniepoint’s technology has powered over 3 million people, offering personal and business banking, payment, credit and business management tools to help them succeed. Moniepoint processed $182 billion in 2023 and currently processes the majority of the POS transactions in Nigeria.

  • Investigate fraud attacks, quantify their impact, and present clear findings that drive prioritisation and response
  • Propose and refine rule-based mitigations, working with fraud operations and engineering to see them through to implementation
  • Build and maintain reporting and dashboards to monitor fraud trends, rule performance, and key operational metrics
  • Work closely with fraud operations, data scientists, engineers, and product managers to ensure analytical insights translate into action
  • Proactively identify emerging patterns and flag risks before they escape

To succeed in this role, you should have

  • Proven experience as a Data Analyst (Fraud), or a similar role (4+ years, can be made up for with accomplishments)
  • Advanced proficiency with SQL. you're comfortable writing complex queries to investigate and slice data across large datasets
  • Experience in fraud, risk, or financial services; you understand how fraud attacks work and how to think about mitigation trade-offs
  • A proactive mindset — you don't wait to be asked; you spot something unusual and you dig in
  • Some exposure to Python or scripting for data manipulation and analysis
  • Proficiency with a BI tool (PowerBI, Looker, Tableau, Superset, Redash, or any other alternative)
  • Strong stakeholder management skills; you can communicate findings clearly to fraud operations, product managers, engineers, and senior leadership — and you know how to influence decisions with data across all of them.
  • Comfort working in fast-paced, cross-functional teams where priorities shift quickly.
  • Proficiency with a spreadsheet tool (Microsoft Excel or Google Sheets, or any other alternative)
  • Enjoy autonomy and a flat structure: we have millions of customers and a flat hierarchy so any individual can have an outsized impact
  • Excellent written and verbal communication skills
  • A drive to learn and master new technologies and techniques
  • A bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, or any other related field

Experience with the following would be a plus

  • Data governance
  • Python or any other scripting language
  • Git or any other version control tool

What we can offer you

  • Culture - We put our people first and prioritise the well-being of every team member. We have built a company where all opinions carry weight and where all voices are heard. We value and respect each other and always look out for one another. Above all, we are human.
  • Learning - We have a learning and development-focused environment with an emphasis on knowledge sharing, training, and regular internal technical talks.
  • Compensation - You’ll receive an attractive salary, pension, health insurance, annual bonus, plus other benefits.

What to expect in the hiring process

  • A preliminary phone call with the recruiter.
  • Technical take-home task (SQL test).
  • Technical Interview with hiring manager.
  • A behavioural interview with the Head of Data Analytics/Science and Fraud Team.

Moniepoint is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees and candidates.

Help Us Support Diversity at Moniepoint

At Moniepoint, we are committed to fostering a diverse and inclusive work environment. We do not discriminate based on gender identity, orientation, or other personal characteristics. To help us track and improve our recruitment efforts and ensure we are meeting our gender inclusion goals, we kindly ask you to answer the following demographic questions. Your responses are voluntary and will not impact your application in any way. Thank you for helping us build a more inclusive team

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