Senior Data Scientist

About the Company

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

Job Summary

Your mission is to develop data science-driven algorithms and applications to improve decisions in business processes like 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 related field
• 5+ years of work experience in analytics, data mining, and predictive data modelling, preferably in the fintech domain
• Strong proficiency in Python and SQL
• Hands‑on experience handling large volumes of tabular data
• Strong analytical skills: ability to make sense of diverse data and its application 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 drive optimization and improvement of 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, revenue generation, and other business outcomes
• Coordinate with different functional teams to make the best use of developed 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 in both data and models

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

Information Technology

Industries

Non-profit Organizations and Primary and Secondary Education

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