Bachelor's degree or equivalent practical experience.
2 years of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data.
2 years of experience managing projects and defining project scope, goals, and deliverables.
Preferred qualifications:
Master's degree or PhD in a quantitative discipline (e.g., Computer Science, Statistics, Mathematics, Physics, Operations Research, etc).
3 years of experience in a large-scale data analysis or data science setting and in abuse and fraud disciplines.
Experience in programming languages (e.g., Python, R, Julia), database languages (e.g. SQL) and scripting languages (e.g., C/C++, Python, Java).
Experience with prompt engineering and fine-tuning LLMs.
Experience applying machine learning techniques to large datasets.
Excellent problem-solving and critical thinking skills with attention to detail in an ever-changing environment.