Data Scientist

Role Overview

• Develop descriptive, predictive, and prescriptive analytical models to support key business decisions related to transactions, pricing optimization, fraud detection, customer behavior, and operational efficiency
• Proactively identify opportunities where data science and Artificial Intelligence can generate business value, proposing analytical initiatives that contribute to increasing transactions, improving profitability, and reducing operational risks
• Take ownership of analytical initiatives from problem definition to implementation, ensuring that analytical models are aligned with business priorities and produce actionable results
• Lead cross-functional collaboration with teams such as Sales, Marketing, Operations, Compliance, Product, and Technology, while clearly communicating analytical insights
• Translate business problems into analytical questions and propose data-driven solutions, demonstrating initiative and a strong problem-solving mindset
• Work closely with the Data Architecture team to ensure reliable, scalable, and well-structured data pipelines that support analytics and AI models
• Validate, monitor, and continuously improve analytical models to ensure accuracy, performance, and long-term reliability
• Communicate insights and recommendations clearly, presenting analytical findings along with practical solutions and business implications
• Promote a culture of data-driven decision-making across the organization by helping business teams understand and adopt analytical tools and model outputs

Requirements

• Bachelor’s Degree in Computer Science, IT, or similar field; a Master’s in Data Science is a plus
• Strong knowledge of statistics, predictive modeling, and machine learning techniques
• Experience with programming languages commonly used in data science (e.g., Python, R, SQL)
• Experience working with large datasets and modern data platforms (data lakes, cloud environments such as AWS, etc.)
• Familiarity with machine learning frameworks and libraries (e.g., Scikit-learn, TensorFlow, PyTorch, or similar)
• Understanding of data preparation, feature engineering, and model evaluation techniques
• Strong analytical thinking and problem-solving capabilities
• Ability to connect analytical work with real business impact
• Curiosity to deeply understand the remittance business, customer behavior, and transaction dynamics
• Ability to translate business problems into analytical questions and data-driven solutions
• Strong communication skills (English and Spanish), capable of explaining complex analytical concepts to non-technical audiences
• Ability to collaborate with cross-functional teams, including Product, Sales, Operations, Marketing, and Compliance
• Curiosity, initiative, and continuous learning mindset

Tech Stack

• AWS
• Cloud
• Python
• PyTorch
• Scikit-Learn
• SQL
• Tensorflow

Benefits

• Performance Bonus
• Company-provided hardware to support remote work
• Diverse and multicultural work environment
• An innovative environment with the structure and resources of a leading multinational
• Opportunities for professional growth aligned with your learning and development