Master's Fellow – Data Scientist, Trade Surveillance, Anomaly Detection

This is a fully remote position, open to applicants in Brazil.

📋 Description

• Comprehensive mapping of proprietary trading operations, encompassing the identification of key points for trade surveillance.

• Creation of a conceptual framework to establish and prioritize CATCHs, indicators, and monitoring signals.

• Execution of detection rules and application of analytical models, incorporating advanced analytics and artificial intelligence to recognize atypical patterns and high-risk behaviors.

• Validation and calibration of CATCHs and models based on historical data analyses.

• Development of governance structures, documentation, and trigger workflows to incorporate the framework into compliance routines.

⛳️ Requirements

• Master’s degree (either in progress or completed).

• Degree in Computer Science, Computer/Software Engineering, Information Systems, Statistics, Applied Mathematics, Electrical Engineering, Data Science, or related fields within the Exact Sciences and Engineering.

• Proficiency in programming and data manipulation: Python or R.

• SQL skills for querying and processing datasets.

• Experience with libraries such as Pandas, NumPy, or similar.

• Knowledge of applied statistics and exploratory data analysis.

• Ability to construct rule-based detection/heuristics.

• Basic model evaluation skills (precision, recall, etc.).

• Familiarity with advanced modeling and AI techniques: both supervised and unsupervised Machine Learning.

• Understanding of anomaly detection methods (outlier detection, clustering, etc.).

• Experience applying models to fraud, risk, or surveillance scenarios.

• Knowledge in data engineering/architecture: distributed processing (Spark, Databricks, or equivalent).

• Capability to build data pipelines.

• Experience with integration into corporate environments (APIs, cloud).

🏝️ Benefits

• Stipend: R$ 9,000.00.

• Availability: 40 hours per week.

• Work arrangement: Remote.