Data Analyst

Job Description

FairMoney is a pioneering mobile banking institution specializing in extending credit to emerging markets. Established in 2017, the company currently operates primarily within Nigeria, and it has secured nearly €50 million in funding from renowned global investors, including Tiger Global, DST, and Flourish Ventures.

In alignment with its vision, FairMoney is actively constructing the foremost mobile banking platform and point-of-sale (POS) solution tailored for emerging markets. The journey began with the introduction of a digital microcredit application exclusively available on Android and iOS devices. Today, FairMoney has significantly expanded its range of services, encompassing a comprehensive suite of financial products, such as current accounts, savings accounts, debit cards, and state-of-the-art POS solutions designed to meet the needs of both merchants and agents.

FairMoney thrives on its diverse workforce, bringing together talent from over 27 nationalities. This multicultural team drives the company’s mission of reshaping financial services for underserved communities. To gain deeper insights into FairMoney’s pivotal role in reshaping Africa’s financial landscape, we invite you to watch an informative video.

Job Description

As a Data Analyst in Collections Operations, you will utilize your expertise in data analysis to support the optimization of collections processes, and loan recovery. You will play a key role in analyzing data related to delinquent accounts, collection strategies, payment behaviors, and providing actionable insights to improve collection efficiency.

Key Responsibilities

• Data Analysis and Reporting: Analyze large datasets related to collections, delinquent accounts, recovery rates, and payment behaviors to provide meaningful insights that optimize collections strategies and improve operational performance.
• Collections Strategy Optimization: Collaborate with collections, credit risk, and operations teams to optimize collections efforts, and identifying opportunities for early intervention.
• Portfolio Monitoring: Track and monitor collection performance metrics, including recovery rates, tracking against collections' targets and provide early warnings of potential risks.
• Automation and Reporting: Automate reporting processes to streamline collections workflows and enhance efficiency using tools such as SQL, Power BI, or Tableau. Provide updates on collections' performance in collections operations forums.
• Collaboration with Cross-Functional Teams: Work closely with collections operations managers, product teams, and risk departments to align data insights with operational strategies and drive improvements in collections performance.
• Ad-hoc Analysis: Provide analytical support for ad-hoc requests related to collections operations, including risk assessments, portfolio reviews, and process improvements.
• Process Improvement: Identify inefficiencies and gaps in collections processes and recommend improvements based on data analysis to enhance recovery rates and reduce operational costs.

Requirements

• Bachelor's degree in Business, Finance, Economics, Statistics, Mathematics, BTech (Business Technology), or related field.

• 2+ years of experience in data analysis, preferably within collections operations, lending, or financial services.

• Proficiency in data analysis tools such as SQL, Excel, Python, R, etc.

• Experience with data visualization tools (e.g., Tableau) to create impactful reports and dashboards.

• Strong knowledge of collections strategies, delinquency management, and recovery metrics.

• Experience in automating reporting and streamlining data processes.

• Understanding of collections processes in a lending environment.

• Knowledge of key collections metrics.

• Ability to collaborate with collections teams and leverage data to optimize recovery strategies and minimize losses.

• Strong analytical and problem-solving skills, with the ability to turn complex data into actionable insights.

• Excellent communication skills, including the ability to present data findings clearly to non-technical stakeholders.

• Attention to detail and a focus on data accuracy and integrity.

• Strong organizational skills, with the ability to manage multiple priorities and meet deadlines.

• Team player with the ability to collaborate effectively across functions.

• Advanced SQL skills for complex data extraction and manipulation.

• Exposure to cloud-based data platforms (e.g., AWS, Google Cloud).

Benefits

• Private Health Insurance
• Pension Plan
• Paid Time Off
• Remote Work Model
• Training & Development Programs

Recruitment Process

1. Screening call with a member of the Talent Acquisition Team.
2. Interview with the Lead, Risk Manager
3. Interview with the Chief Credit Officer.