Responsibilities:

• Assist in data collection, cleaning, and preprocessing for the finance team
• Support senior analysts in creating reports and dashboards.
• Perform basic data analysis tasks.

Requirements:

• Basic knowledge of SQL and data visualization tools.
• Familiarity with Metabase, QuickSight, or similar tools.
• Understanding of data analysis techniques.
• Willingness to learn and grow within the team.
• Ability to say 'I don't know' and willingness to research and find solutions.

Bonus Requirements:

1. Candidates must be either Actuaries or Computer Scientists. Regardless of their primary background, they must have a solid understanding of computer science.
2. Fintech Experience: Prior experience in the fintech industry is essential.

Bonus Qualifications:

1. Country-Specific Fiscal Knowledge: Candidates from the following countries will have a significant advantage if they possess basic fiscal knowledge relevant to their country:
• Mexico: Basic knowledge of the Mexican Fiscal SAT.
• Brazil: Basic knowledge of Brazilian fiscal regulations.
• Colombia: Basic knowledge of Colombian fiscal regulations.
2. Finance Audit Experience: Candidates must have lived through a finance audit and understand the processes involved.
3. Understanding of Financial Conciliation: Strong understanding of financial conciliation processes.
4. Experience in Credit Card and Payments: Prior experience with credit card and payment systems will be a plus.
5. Risk Modeling in Latin America: Experience in risk modeling specific to the Latin American market is highly desirable.
6. Open Mindset: Candidates should have an open mind and be willing to create new and innovative solutions.

Bonus Requirements for Data Roles in Finance and Risk:

1. Data Analysis and Visualization: Proficiency in SQL and data visualization tools (e.g., Metabase, QuickSight). Ability to analyze financial data and create actionable insights.
2. Experience with Financial Data Systems: Familiarity with financial data systems and tools, such as those used for managing transactions, auditing, and compliance.
3. Regulatory Compliance: Understanding of regulatory requirements and compliance standards in the financial sector, especially those relevant to Latin America.
4. Machine Learning and Risk Modeling: Experience with machine learning algorithms (e.g., XGBoost, CatBoost) and their application in risk modeling and fraud detection.
5. Data Integrity and Quality: Strong emphasis on maintaining data integrity and quality, especially in financial datasets.
6. Python and R Programming: Proficiency in programming languages commonly used for financial modeling and analysis, such as Python and R.
7. Stakeholder Communication: Ability to communicate complex data findings to non-technical stakeholders, including finance and executive teams.
8. Problem-Solving Skills: Strong problem-solving skills and ability to think critically about data and its application in solving business problems.
9. Agile and Lean Methodologies: Experience working in agile and lean environments, common in startups, to adapt quickly to changing business needs.