TL;DR

Machine Learning Engineer II: Building production ML models and risk management tools to minimize fraud exposure and improve e-commerce shopping experiences with an accent on real-time fraud pattern research. Focus on improving the %hirify_global% Commerce Protection Platform and strengthening the machine-learning pipeline.

Location: Hybrid in Budapest, Hungary

Company

%hirify_global% helps merchants confidently grow their businesses by building trusted relationships with their customers through advanced technology and a dedicated team.

What you will do

Research emerging fraud patterns in real-time with the Risk Intelligence team.
Improve components of the %hirify_global% Commerce Protection Platform.
Build production machine learning models that identify fraud.
Write production and offline code in Python and PySpark.
Work with distributed data pipelines.
Collaborate with engineering teams to strengthen the machine-learning pipeline.

Requirements

A degree in computer science or a comparable analytical field.
3+ years of post-undergrad work experience required.
Strong verbal and written communication skills.
Strong machine learning and statistical background.
Write code and review others' in a shared codebase in Python.
Practical SQL knowledge.

Nice to have

Previous work in fraud, payments, or e-commerce.
Data analysis in a distributed environment.
Passion for writing well-tested production-grade code.
A Master's Degree or PhD.

Culture & Benefits

Stock Options.
Annual Performance Bonus or Commissions.
Pension matched up to 3%.
‘Day one’ access to great health insurance scheme.
Enhanced maternity and paternity leave (12 weeks full-pay for mums & dads).
Dedicated learning budget through Learnerbly.