The Payhippo mission is to make financial services seamless for African SMEs. Payhippo is Africa’s credit-led SME neobank. We’ve completed stage one with our 3-Hour Loan in Nigeria and just started beta testing our banking app with merchants. Growing 25% month on month, we have a 97% repayment rate in Nigeria. There are 40m SMEs in Nigeria alone. Our repayment rate is so high because most of these businesses are creditworthy, but traditional banks and lenders often don’t lend to them because there are no credit scores and collateral requirements are too high. That’s why we assess businesses, build their Payhippo Scores, and provide financing to them. We’re growing so fast because our 3 co-founders have fintech and lending experience in Nigeria. Zach worked at Lidya (a venture-backed digital SME lender in Africa), Chioma worked in microfinance policy, and Uche was a full-stack engineer at consumer lending fintech Earnest. Here is more information about Payhippo:
- Seed Announcement: TechCrunch
- Y Combinator Announcement: Business Insider
- Preseed Announcement: TechCabal
- Website: Payhippo.ng
We are looking for a Data Analyst responsible for collecting, analyzing, and interpreting data to help unblock multiple teams. Your insights will drive informed business decisions, optimize strategies, and enhance the user experience of our products and services. The ideal candidate will have a strong analytical mindset, proficiency in statistical analysis, and the ability to effectively communicate complex findings to stakeholders. Location: Nigeria | Open to all African countries Status: Remote | Full-time
Data Collection and Cleaning:
- Identify, collect, and organize relevant data from various sources, including internal databases, banking app usage logs, external APIs, and third-party vendors.
- Perform data cleaning, validation, and transformation to ensure accuracy and consistency.
Data Analysis and Interpretation:
- Develop and implement data models, algorithms, and statistical techniques to extract meaningful insights from raw data.
- Analyze lending portfolios, borrower profiles, and lending trends to identify risks, opportunities, and areas for improvement.
- Analyze banking app usage patterns, user behavior, and customer satisfaction metrics to optimize the user experience and drive app engagement.
- Conduct in-depth statistical analysis, including regression models, predictive modeling, and data mining, to support business decisions, risk assessment, and strategic planning.
- Collaborate with cross-functional teams to design and conduct experiments to test hypotheses, validate business strategies, and enhance the app’s features and functionalities.
Reporting and Visualization:
- Prepare and present comprehensive reports, dashboards, and visualizations to communicate analytical findings and recommendations to key stakeholders.
- Develop automated reporting systems and tools to streamline data analysis processes and improve efficiency.
- Monitor and track lending metrics, banking app performance, key performance indicators (KPIs), and other relevant data points to identify performance trends and deviations.
Data Quality and Integrity:
- Monitor data quality, identify data anomalies, and implement corrective actions to maintain data integrity and accuracy.
- Establish and maintain data governance practices, including data documentation, data dictionaries, and data lineage, for both lending and banking app data.
Collaboration and Communication:
- Collaborate with stakeholders, including business managers, risk analysts, product managers, and IT teams, to understand their data needs and provide analytical support.
- Clearly communicate complex analytical concepts and findings to both technical and non-technical audiences.
- Participate in cross-functional projects and initiatives to enhance data analytics capabilities, improve lending strategies, and enhance the user experience of the banking app.
- 3+ years experience as a Data Analyst or similar role, preferably in the lending or financial services industry with exposure to banking app data.
- Solid experience with Big Query
- Strong proficiency in data analysis tools such as SQL, Python, R, or similar programming languages.
- Proficiency in data visualization tools such as Tableau, Power BI, or similar platforms.
- Solid understanding of statistical concepts, regression analysis, and predictive modeling techniques.
- Experience with data cleaning, transformation, and manipulation using tools like Pandas, Excel, or similar software.
- Familiarity with database management systems (DBMS) and data querying languages.
- Knowledge of lending operations, credit risk assessment, loan portfolio management, and banking app analytics is desirable.
- Excellent problem-solving skills and attention to detail.
- Strong verbal and written communication skills to effectively convey complex findings to diverse stakeholders.
- Ability to work independently and collaboratively in a fast-paced environment.
- Strong organizational and time management skills to handle multiple projects and meet deadlines.
How to Apply:
Please send your CV to email@example.com with the title of the role and your first then last name. Please share a portfolio of your work if applicable to your skills and experience.