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- Tasks: Analyse data to improve loan eligibility and manage credit risk.
- Company: Join M-KOPA, a leader in financial inclusion and innovation.
- Benefits: Flexible work options, career development, and a supportive environment.
- Why this job: Make a real impact on millions by shaping credit access for the unbanked.
- Qualifications: Strong analytical skills, experience with Python and SQL, and teamwork abilities.
- Other info: Be part of a fast-growing team recognised for its social impact.
The predicted salary is between 28800 - 48000 £ per year.
We are looking for an Analyst to help drive M-KOPA’s mission of building transformative lifetime financial partnerships with our customers. This role offers the opportunity to directly impact millions of customers' access to credit by building underwriting frameworks. You will be a member of a small team with the big responsibility of continuously improving M-KOPA’s loan offers and eligibility criteria in order to drive growth while managing credit losses and margins. You'll work cross-functionally with engineers, data scientists, other analysts, growth managers, and commercial stakeholders across multiple countries.
We're building the future of financial inclusion, and data-driven decision making is at the heart of our mission. Our team combines analytical rigor with deep market understanding to develop loan eligibility and pricing for customers who have traditionally been excluded from formal financial services. We foster a low-ego environment where diversity, innovation, and collaboration drive both commercial growth and social impact. You'll be empowered to make data-driven decisions and clear cases for prioritisation of solutions in a domain that you have a high degree of ownership over. You'll be joining a newly established team that's rapidly expanding our credit and underwriting capabilities. We are looking for someone who loves analysing complex data and solving challenging, ambiguous data problems — if that sounds like you, you might be a fit!
In this role, you would be responsible for:
- Analysing M-KOPA's repayments data and other data sources to continuously improve our loan eligibility criteria while managing credit risk
- Refining loan pricing based on credit analysis and customer behaviour
- Testing new types of loans to understand customer demand and credit performance
- Monitoring credit performance to detect risk shifts and quantify margin impact
- Testing the predictiveness of new data sets for the purposes of eligibility criteria
- Using Python, SQL, and other tools for data analysis to drive insights
- Working with data scientists to leverage machine learning models as part of loan eligibility decisions
This role can be remote or hybrid, but candidates must be located within our time zones (UTC -1 to UTC+3) to ensure effective collaboration with teams across our multiple locations.
Your application should demonstrate:
- Several years in roles with significant analytical components
- Strong statistical modelling and quantitative analysis skills, including the ability to conduct your own analysis of unstructured data
- Fluency in Python, SQL, and other relevant tools for data analysis
- Experience translating complex data insights into actionable business strategies
- Ability to work cross-functionally with product, engineering, and commercial teams
- Strong data communication skills — written, oral, and visual
- Strong interpersonal and collaboration skills
- (Nice to have) Experience in credit, underwriting, or lending analytics
Credit accessibility and affordability are at the core of this role. You’ll join a small, high-performing team where every day brings new problems to solve and analyses that shape our lending strategy. If this excites you, we’d love to hear from you.
At M-KOPA, we empower our people to own their careers through diverse development programmes, coaching partnerships, and on-the-job training. We support individual journeys with family-friendly policies, prioritise well-being, and embrace flexibility. Join us in shaping the future of M-KOPA as we grow together. Explore more at m-kopa.com.
M-KOPA is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained staff. Women, minorities, and people with disabilities are strongly encouraged to apply. M-KOPA explicitly prohibits the use of Forced or Child Labour and respects the rights of its employees to agree to terms and conditions of employment voluntarily, without coercion, and freely terminate their employment on appropriate notice. M-KOPA shall ensure that its Employees are of legal working age and shall comply with local laws for youth employment or student work, such as internships or apprenticeships. M-KOPA does not collect/charge any money as a pre-employment or post-employment requirement. This means that we never ask for ‘recruitment fees’, ‘processing fees’, ‘interview fees’, or any other kind of money in exchange for offer letters or interviews at any time during the hiring process.
Applications for this position will be reviewed on a rolling basis. Shortlisting and interviews will take place at any stage during the recruitment process. We reserve the right to close the vacancy early if a suitable candidate is selected before the advertised closing date. If your application is successful M-KOPA undertakes pre-employment background checks as part of its recruitment process, these include; criminal records, identification verification, academic qualifications, employment dates and employer references.
Data Analyst - Credit Eligibility employer: M Kopa
Contact Detail:
M Kopa Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst - Credit Eligibility
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at M-KOPA. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Prepare for interviews by practising common data analyst questions. Think about how your skills in Python and SQL can solve real problems at M-KOPA. Show them you’re not just a number cruncher but a problem solver!
✨Tip Number 3
Don’t forget to showcase your analytical projects! Whether it’s a personal project or something from your previous job, having tangible examples of your work can really impress the hiring team.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in being part of the M-KOPA mission.
We think you need these skills to ace Data Analyst - Credit Eligibility
Some tips for your application 🫡
Show Off Your Analytical Skills: Make sure to highlight your experience with data analysis in your application. We want to see how you've tackled complex data problems and the tools you've used, like Python and SQL. Don’t just list your skills; give us examples of how you’ve applied them!
Tailor Your Application: Take a moment to customise your application for this role. Mention specific experiences that relate to credit eligibility and underwriting frameworks. We love seeing candidates who understand our mission and can connect their background to what we do at M-KOPA.
Communicate Clearly: Strong communication is key! Whether it’s written or visual, make sure your application reflects your ability to convey complex data insights in a straightforward way. We appreciate clarity and conciseness, so keep it engaging and easy to read.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our team and contributing to our mission of financial inclusion!
How to prepare for a job interview at M Kopa
✨Know Your Data
Make sure you brush up on your data analysis skills, especially in Python and SQL. Be prepared to discuss specific projects where you've used these tools to derive insights or solve problems, as this will show your practical experience and understanding of the role.
✨Understand the Business
Familiarise yourself with M-KOPA's mission and how they use data to drive financial inclusion. Think about how your analytical skills can contribute to improving loan eligibility criteria and managing credit risk. This will demonstrate your alignment with their goals.
✨Prepare for Scenario Questions
Expect questions that ask you to analyse hypothetical data scenarios or past experiences. Practice articulating your thought process clearly, as this will showcase your problem-solving abilities and how you approach complex data challenges.
✨Show Your Collaborative Spirit
Since the role involves working cross-functionally, be ready to share examples of how you've successfully collaborated with different teams. Highlight your interpersonal skills and how you can contribute to a low-ego environment that values diversity and innovation.
