At a Glance
- Tasks: Investigate fraud, quantify impacts, and present findings to drive action.
- Company: Join Moniepoint, Africa's second-fastest growing financial services platform.
- Benefits: Attractive salary, health insurance, annual bonus, and a focus on well-being.
- Other info: Enjoy a flat structure and a culture that values every voice.
- Why this job: Make a real impact in fraud prevention while working with cutting-edge technology.
- Qualifications: 4+ years as a Data Analyst with strong SQL skills and fraud knowledge.
The predicted salary is between 45000 - 55000 £ per year.
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
Data Analyst - Fraud employer: Moniepoint
Moniepoint is an exceptional employer that fosters a collaborative and innovative work environment in the heart of London. With a strong emphasis on employee growth, competitive compensation, and comprehensive health benefits, we empower our team to make a meaningful impact on the financial aspirations of millions. Join us to be part of a supportive culture that values well-being and professional development.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analyst - Fraud
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Moniepoint!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Analyst - Fraud at Moniepoint.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Moniepoint.
✨Apply Directly through Our Website
When you find a suitable opening like Data Analyst - Fraud at Moniepoint, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Analyst - Fraud
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Moniepoint, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Moniepoint. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Moniepoint
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Moniepoint!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
