Data Analyst

Summary

Join Feedzai's Customer Success Team as a Data Analyst to leverage your technical skills in data analysis, ETL, and visualization. You will investigate fraud patterns, propose and implement rules to prevent fraud attacks, and collaborate with Data Scientists and Risk Strategy SMEs. This role involves working with large datasets using Python, SQL, and Spark on cloud-based platforms. You will analyze fraud trends, design and implement rules to capture fraudulent activities, and monitor risk strategy performance. The ideal candidate possesses 1+ years of experience in a data analyst role and a Bachelor's degree in a related field. Feedzai offers a dynamic and supportive work environment.

Requirements

• 1+ years of experience in a data analyst or related role
• Bachelor’s degree in computer science, mathematics, statistics or in a related field
• Knowledge of scripting/programming for data analysis and ETL pipelines (e.g., Python, PySpark and SQL)
• Knowledge of reporting & data visualization techniques
• Experience with data visualization tools (e.g. Tableau, Google Data Studio)
• Good verbal and written communication skills, suitable to working with internal and external partners
• Ability to communicate findings in a clear way to key stakeholders and devise action plans from those findings

Responsibilities

• Work with project teams to establish business questions and data requirements
• Work with risk consultants and data scientists to perform data mapping and data quality validation
• Design and write programs for data cleaning, extraction, segmentation, and statistical analysis on large population datasets using languages such as Python, SQL and Spark on cloud-based computing platforms
• Analyze and draw insights from fraud trends & market trends, and support industry wide analytical studies
• Design, implement, test and tune rules to capture fraudulent and suspicious activities
• Monitor risk strategy performance and deep dive on performance issues

Preferred Qualifications

• Experience working together with Data Science teams is a plus
• Experience in Financial Crime or Payments is highly valued