Senior Machine Learning Engineer

Mangopay

. Build and improve fraud detection solutions for fraudulent payments, identity theft, and account takeover .

Posted 10/30/2026full-timeWarsaw • PolandSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and improving fraud detection solutions through advanced machine learning techniques, data analysis, and software engineering practices. Proficient in developing scalable ML services and leading data science projects that drive measurable business impact.

Highest-signal resume keywords

Machine Learning AlgorithmsPython ProgrammingSQL SkillsData EngineeringFraud Detection Solutions

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningFeature EngineeringModel EvaluationStatistical AnalysisData Analysis

Soft Skills

Analytical SkillsProblem-Solving SkillsCommunication SkillsBusiness Mindset

Tools & Technologies

PandasNumPyScikit-LearnAWSDocker

Industry Keywords

Fraud DetectionFintechBanking RiskCreditIdentity Theft

Tech Stack

Tools & technologies

ApacheAWSDockerKafkaKubernetesNumpyPandasPythonScikit-LearnSnowflakeSQLTerraform

About the role

Key responsibilities & impact

Build and improve fraud detection solutions for fraudulent payments, identity theft, and account takeover
Investigate fraud patterns using transactional and behavioural data
Research algorithms and data sources
Develop, evaluate, and maintain machine learning models processing millions of transactions
Build and maintain data pipelines and datasets for feature engineering, model training, and real-time inference
Develop and operate production ML services for reliability, scalability, performance, and security
Build internal tools and workflow automations
Lead end-to-end data science projects from opportunity identification and solution design through measurable business impact

Requirements

What you’ll need

At least 5 years of professional experience in Data Science, applied Machine Learning, or a closely related field
Strong understanding of machine learning algorithms, statistics, feature engineering, model evaluation, and validation techniques
Excellent Python skills, including pandas, NumPy, and scikit-learn
Strong SQL skills and experience working with large, complex datasets
Good software engineering practices, including clean code, testing, version control, and maintainability
Solid understanding of software architecture and design principles
Practical experience in Machine Learning Engineering or Data Engineering
Willingness and ability to develop expertise in the less familiar area
Strong analytical and problem-solving skills
Pragmatic business mindset and excellent communication skills
Very good English and Polish language skills
A degree in mathematics, computer science, quantitative methods, econometrics, or engineering is nice to have but not mandatory
Nice-to-have experience with AWS, Amazon SageMaker, Kubernetes, Docker, CI/CD, Apache Kafka, Terraform, Snowflake, dbt, n8n, AI agents, generative AI, fintech, banking risk, credit, or fraud detection

Benefits

Comp & perks

Opportunity to work on machine learning problems with direct business impact
Ownership of solutions from initial exploration through production
Opportunity to combine Data Science with real-world engineering
Opportunity to deepen expertise in Machine Learning or Data Engineering
Opportunity to shape how data and ML systems are developed and maintained
Continuous learning
HR call, take-home test, and case study interview process