BAP - Data Analyst

• Assist with the development, maintenance, and improvement of SQL-based data pipelines and analytical workflows.
• Support data standardization and normalization initiatives, including activities such as address parsing and entity resolution.
• Help develop and optimize data models, dashboards, reports, and other analytical outputs.
• Conduct ad-hoc data analysis under the guidance of senior team members and communicate findings clearly to the wider team.
• Assist with monitoring data quality and implementing validation rules to improve the reliability and consistency of datasets.
• Support data preparation, transformation, and analysis across large-scale datasets.
• Collaborate with colleagues on cross-functional data initiatives and contribute to the delivery of shared analytical objectives.
• Develop practical understanding of data analytics, risk management, fraud detection, and data-driven business processes.
• Document analytical work and contribute to maintaining consistent and reusable data processes.

Requirements:

• Currently pursuing a Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative discipline.
• Solid SQL skills, with familiarity with Hive SQL or Spark SQL considered an advantage.
• Basic proficiency in at least one scripting or programming language, with Python preferred.
• Strong interest in data analytics, risk management, fraud detection, data quality, or related fields.
• Analytical mindset with strong logical reasoning and attention to detail.
• Good communication skills and the ability to explain analytical findings clearly.
• Eagerness to learn, take initiative, receive feedback, and develop new technical skills.
• Ability to collaborate effectively with senior team members and cross-functional stakeholders.
• Comfortable working with structured processes while remaining proactive when investigating data issues or patterns.
• Availability for at least 3 days per week and commitment to a minimum 3-month internship.

Benefits:

• Hands-on experience working with real-world, large-scale datasets and data analytics projects.
• Opportunity to develop practical SQL, Python, data modeling, data quality, and analytical skills.
• Exposure to data standardization, normalization, risk analytics, and fraud-related use cases.
• Mentorship and guidance from experienced data professionals.
• Opportunity to collaborate with talented colleagues in a global and user-focused technology environment.
• Exposure to fast-paced projects and cross-functional data initiatives.
• Opportunities for continuous learning, professional development, and career growth.
• Competitive compensation and applicable company benefits, subject to local terms.
• Work-from-home arrangement, depending on the requirements of the relevant business team.
• Flexible internship structure requiring a minimum of 3 days per week, with a minimum 3-month commitment.