Senior Data Scientist

Meniga; Warszawa; Hybrid; PLN 180,000 - 280,000; Full time

Benefits offered by this job

Health and Benefits: Private health

Hybrid working

Growth opportunities

Performance-based bonus

Job summary

Meniga is hiring a Senior Data Scientist to work on the enrichment engine that turns raw banking data into clean merchant, category and location signals. The role focuses on behavioural features, scores and segments powering personalisation, CRM and AI agents for millions of customers.

You will work in Python, advanced SQL and dbt, with an event warehouse (ClickHouse or equivalent) and Airflow pipelines, handling real-world banking data and QA/synthetic datasets.

Qualifications

• 5+ years as a data scientist in banking, lending, cards, wealth or fintech
• Hands-on work with transactional data, not just clickstream
• Ability to build explainable models and document methods

Responsibilities

• Advance Transaction and Merchant Enrichment: improve classification and merchant-matching models and define quality metrics
• Design Behavioral Features: turn banking event streams into meaningful signals for models and rules
• Build Scores Banks Can Defend: productionise scores with definitions, validation and drift checks
• Define the Statistical Building Blocks: specify how signals behave, remain calibrated and explainable

Skills

Data science

Python

SQL

Tools

dbt

Airflow

ClickHouse

Job description

Meniga is a leading hyper-personalisation banking platform, our vision is to enable banking that is genuinely personal, proactive, and valuable to every customer. We give banks the data infrastructure to make digital banking genuinely personal, proactive and valuable, not generic. Today we enrich 45 million transactions a day and serve 100+ million banking customers across 165 banks in 30+ countries. We are a global leader in transaction enrichment, AI-powered insights and hyper-personalisation for large financial institutions, a multiple Finovate ''Best of Show'' winner, and featured on CNBC's 2025 list of top UK fintechs. We're a global team with offices in London, Reykjavik, Warsaw, and Cairo.

We are hiring a Senior Data Scientist to work on the science at the core of our platform. Our enrichment engine turns raw, messy transaction data into clean merchant, category and location information. Our intelligence layer builds on those signals to understand each customer's financial life: the behavioural features, scores and segments that power personalisation, CRM, advisory and AI agents for 100+ million banking customers. Your focus may sit on enrichment, on customer intelligence, or across both.

This is high-impact, high-trust work: banks run what you build in production and defend it to auditors and regulators, so everything you ship must be explainable, documented and stable. Day to day you will work in Python, advanced SQL and dbt, with an event warehouse (ClickHouse or equivalent) and Airflow pipelines, on real-world banking data and synthetic datasets used for QA and demos.

To qualify, you will need 5+ years as a data scientist in banking, lending, cards, wealth or fintech, with work shipped on transactional data, not only clickstream. This is a hands-on scientific role rather than an LLM-chatbot, data-engineering or AML position: AI agents and user interfaces consume the signals and scores you build, and your job is to make them true, stable and shippable.

Key Responsibilities

• Advance Transaction and Merchant Enrichment: Improve the classification and merchant-matching models behind our enrichment engine, and define the quality, coverage and confidence metrics that let banks trust each merchant, category and location signal.
• Design Behavioural Features: Turn banking event streams into meaningful financial signals, income stability, spend volatility, liquidity, balance trajectory, reproducible, documented and ready to use in models and rules.
• Build Scores Banks Can Defend: Productionise financial-health, churn and propensity scores and behavioural segments. Every score ships with a clear definition, validation and drift checks, and an explanation a risk or compliance stakeholder can read.
• Define the Statistical Building Blocks: Banks configure their own rules and metrics on top of your signals. You define what each function means, how it behaves on sparse or messy data, and how it stays calibrated and explainable.

Personal Attributes

• You judge methods by whether they make the product true and defensible, a well-documented metric beats an impressive model.
• Definitions, lineage and reproducibility are your default working style, not overhead.
• You make progress with ambiguous, incomplete data and are honest about what it can and cannot tell you.
• You work well across product, CRM, advisory and engineering, and you win arguments with evidence, not jargon.

What We Offer

• Health and Benefits: Private healthcare, fitness allowance and leave benefits.
• Supportive Work Environment: Work-life balance, hybrid working, meal allowance, team-building events and reimbursement for internet/phone subscriptions.
• Growth Opportunities: A front-row seat in a scaling fintech, international projects and career advancement.
• Financial Rewards: Competitive salary, performance-based bonus and ESOPs.