FairMoney is a pioneering mobile banking institution specializing in extending credit to emerging markets. Established in 2017, the company operates primarily within Nigeria and 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, and today FairMoney’s suite of financial products includes current accounts, savings accounts, debit cards, and state‑of‑the‑art POS solutions for merchants and agents.

FairMoney thrives on its diverse workforce, bringing together talent from over 27 nationalities. This multicultural team drives the mission of reshaping financial services for underserved communities.

Job Summary

Your mission is to develop data science‑driven algorithms and applications to improve decisions in business processes such as risk and debt collection, offering the best‑tailored credit services to as many clients as possible.

Requirements

• Strong background in Mathematics, Statistics, Econometrics, Computer Science, or a related field.
• 5+ years of experience in analytics, data mining, and predictive data modelling, preferably in the fintech domain.
• Proficiency in Python and SQL.
• Hands‑on experience handling large volumes of tabular data.
• Strong analytical skills: ability to derive insights and relate them to specific business problems.
• Confidence working with key machine learning algorithms (GBM, XG‑Boost, Random Forest, Logistic Regression).
• Experience building and deploying models around credit risk, debt collection, fraud, and growth.
• Track record of designing, executing, and interpreting A/B tests in a business environment.
• Strong focus on business impact and experience driving it end‑to‑end using data science applications.
• Strong communication skills.
• Passion for all things data.

Tool Stack

• Programming language: Python
• Production: Python API deployed on Amazon EKS (Docker, Kubernetes, Flask)
• ML: Scikit‑Learn, LightGBM, XGBoost, shap
• ETL: Python, Apache Airflow
• Cloud: AWS, GCP
• Database: MySQL
• DWH: BigQuery, Snowflake
• BI: Tableau, Metabase, dbt
• Streaming Applications: Flink, Kinesis

Role and Responsibilities

• Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
• Mine and analyze data from company databases and external sources to optimize risk strategies, product development, marketing techniques, and other business decisions.
• Assess the effectiveness and accuracy of new data sources and data gathering techniques.
• Use predictive modelling to increase and optimize customer experiences and revenue generation.
• Coordinate with functional teams to maximize data science applications.
• Develop processes and tools to monitor and analyze model performance and data quality.
• Apply advanced statistical and data mining techniques to derive patterns from the data.
• Own data science projects end‑to‑end and proactively drive improvements.

Benefits

• Paid Time Off (25 days Vacation, Sick & Public Holidays)
• Family Leave (Maternity, Paternity)
• Training & Development budget
• Paid company business trips (not mandatory)
• Remote work

Recruitment Process

• Screening call with Senior Recruiter
• Home Test assignment
• Technical interview
• Interview with the team and key stakeholders.

Seniority level

Mid‑Senior level

Employment type

Full‑time

Job function

Engineering and Information Technology

Location

Greater London, England, United Kingdom