Data Scientist - Fintech ML for Payment Performance | Hybrid

Checkout.com

Greater London

Hybrid

GBP 70,000 - 100,000

Full time

14 days+
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Benefits offered by this job

Hybrid working model

Job summary

Checkout.com in London is seeking a Data Scientist to join our ambitious team, focused on discovering, designing, and experimenting with new estimators, models and features to boost payment performance across our merchant portfolio.

You will collaborate with Data Scientists, Product and Engineering to protect customer lifetime value through network intelligence, and ensure safe model launches with robust observability. The role offers a hybrid work model.

Qualifications

  • 3+ years of experience building ML models to solve business problems.

Responsibilities

  • Contribute to the research and development of new ML models and estimators to boost core Acceptance Rate performance.
  • Design and implement experiments to manage time-based data leakage and robust evaluation.
  • Collaborate with Data Scientists and engineers to productionise ML features, models and evolve our evaluation and monitoring frameworks.
  • Write high-quality, interpretable Python code for feature engineering and model training, contributing directly to our core products.
  • Communicate hypotheses, evaluation results, and monitoring dashboards clearly to both technical and non-technical audiences.

Skills

Machine learning development
Python
Feature engineering
Statistics (Bayesian/Frequentist)
Experiment design
LLMs for coding

Tools

Docker
Databricks
Cloud platforms (GCP/AWS)
Unix shell

Job description

Checkout.com in London is seeking a Data Scientist to join our ambitious team, focused on discovering, designing, and experimenting with new estimators, models and features to boost payment performance across our merchant portfolio.

You will collaborate with Data Scientists, Product and Engineering to protect customer lifetime value through network intelligence, and ensure safe model launches with robust observability. The role offers a hybrid work model.

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