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Team: Analyst
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Scientist based in Brazil.
In this role, you will join a highly specialized data science team focused on combating financial crime and enabling trust in digital transactions at a global scale. You will work at the intersection of machine learning, data engineering, and customer-facing problem solving, helping financial institutions detect and prevent risk in real time. The position involves working directly with large-scale, complex datasets, transforming raw data into actionable insights and production-ready models. You will collaborate closely with clients as well as internal teams such as Product and Research to continuously improve risk detection systems. The environment is fast-paced, mission-driven, and highly collaborative, with strong exposure to real-world impact in global financial ecosystems. This is a hands-on role where technical depth, analytical thinking, and communication skills come together to solve meaningful, high-stakes problems.
Accountabilities:
- Analyze, clean, and validate large-scale client datasets to ensure data quality and usability for modeling and risk analysis.
- Perform data preprocessing and feature engineering using tools such as Python, shell scripting, and distributed data frameworks.
- Develop, train, and optimize machine learning models to improve fraud detection and risk prevention performance.
- Iterate on model features and parameters to enhance accuracy, robustness, and scalability of solutions.
- Communicate analytical findings and model results to project managers and stakeholders, supporting data-driven decision-making.
- Collaborate directly with clients’ data scientists, engineers, and risk teams to deploy and refine risk management solutions.
- Work cross-functionally with internal teams (Product, Research, Engineering) to improve methodologies, tools, and best practices.
- Contribute to the deployment and continuous improvement of data science solutions in production environments.
- Master’s or PhD in Computer Science, Engineering, Statistics, Mathematics, Physics, or related fields.
- Strong experience in machine learning concepts, including model training, evaluation, and overfitting prevention.
- Proficiency in Python and at least one of Java or Scala, with strong scripting skills (bash/shell).
- Experience working with big data technologies such as Spark, Hadoop, or similar frameworks.
- Solid understanding of data preprocessing, feature engineering, and model optimization techniques.
- Knowledge of statistics and data visualization is a plus.
- Familiarity with tree-based models (e.g., Random Forest, XGBoost, LightGBM) and/or deep learning is a plus.
- Understanding of performance optimization and system/runtime monitoring is an advantage.
- Strong communication skills with the ability to explain complex technical findings clearly to both technical and non-technical audiences.
- Ability to work in collaborative, client-facing, and fast-paced environments.
- Remote work model based in Brazil.
- Opportunity to work on large-scale, real-time financial risk systems impacting billions of transactions globally.
- Exposure to cutting-edge machine learning and fraud detection technologies.
- Collaborative, international, and mission-driven work environment.
- Strong learning culture with opportunities to grow in advanced data science and AI domains.
- Cross-functional collaboration with top-tier engineering, product, and research teams.
- High-impact work contributing directly to financial security and digital trust.
Requirements:
Benefits:
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