Bachelor's degree or equivalent practical experience.
2 years of experience in data analysis or data science, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data.
Experience with one or more of the following languages: SQL, R, Python, or C++.
Preferred qualifications:
Master's degree in a quantitative discipline.
2 years of experience in the Payments industry, working on risk or fraud management.
Knowledge in one or more of the following areas: statistical analysis and Machine Learning libraries (e.g., R, Scikit-learn,Tensorflow), programming languages (e.g., Python, C/C++), Large Language Models (LLMs) or Generative AI.
Ability to identify workflow pain points, optimize, automate and scale processes.
Excellent communication skills and comfortable interacting with internal and external stakeholders.
Excellent problem-solving and critical thinking skills with attention to detail in an ever-changing environment.