Senior Data Science Analyst

Responsibilities:

Design, develop, and deploy advanced machine learning models for fraud detection.

Have in-depth knowledge in Graph Neural Networks (GNN), Transformers, Variational AutoEncoders, Deep Learning Models and advanced ML concepts.

Perform data analysis, feature engineering, and statistical modeling on large-scale transactional datasets.

Collaborate with compliance, risk, and operations teams to translate requirements into actionable data science solutions.

Build and maintain data pipelines using SQL, Python, and AWS services (SageMaker, Redshift, S3, Lambda).

Support the integration of ML models into production environments, including Feedzai.

Monitor and evaluate model performance, prepare reports, and recommend improvements and ensure solutions align with regulatory standards and organizational policies.

Skills:

Education: PhD in Statistics, Machine Learning or Deep Learning.

Experience: 1+ years of experience in Data Science and experience in FinTech, Payments, Banking is preferred.

Strong programming and analytical skills with Python, SQL, and statistical techniques.

Experience in applying machine learning methods such as classification, clustering, anomaly detection, and NLP.

Implementing existing research / developing novel algorithms, technical solutions to combat fraud and anti-money laundering (AML) use cases.

Exposure to Feedzai or similar fraud detection platforms and AWS experience is preferred.

Strong communication and collaboration skills, with the ability to work across cross-functional teams.