Data Scientist

Meniga is a leading hyper-personalisation banking platform giving banks the data infrastructure to make digital banking genuinely personal and proactive. They enrich 45 million transactions a day and serve 100+ million banking customers across 165 banks in 30+ countries. They specialize in transaction enrichment, AI-powered insights, and hyper-personalisation for large financial institutions.

• Minimum 2-3 years of experience as a data scientist.
• Experience in banking, lending, cards, wealth, or fintech, especially on transactional data.
• Strong programming skills in Python (including pandas) and SQL.
• Experience with event/analytical warehouses such as ClickHouse.
• Familiarity with pipeline tools like Airflow.
• Experience with production ML including model and drift monitoring tools like MLflow.
• Ability to produce analysis others can rerun and to communicate with product, CRM, and engineering teams.
• Some exposure to audit and explainability requirements.
• AI-native usage of tools like Cursor and Claude Code.
• Full English language proficiency.

Nice to have:

• Practical experience with dbt, Airflow, or Spark.
• Experience in real-time or event-driven scoring.
• Knowledge of fraud, credit risk, or financial-health models.
• Experience with personalization, next-best-action, or marketing decisioning.
• Use of synthetic data for testing (personas, edge cases).

• Support transaction and merchant enrichment models and contribute to quality and confidence metrics for banking signals.
• Build behavioural features from banking event streams that are reproducible, documented, and ready for models and rules.
• Help ship financial-health, churn, and propensity scores with clear definitions, validation, drift monitoring, and explainability.
• Apply statistical methods, implement and test functions on sparse or messy data, and address calibration or explainability issues.
• Work within Python, SQL, dbt, event warehouses (ClickHouse or equivalent), and Airflow pipelines on real and synthetic banking data.