Full-Time Data Scientist Specialist

• Developing and implementing real-time scoring models: Design and implement solutionsto quantify the risk level of transactions and credit operations.
• Optimizing user onboarding: Build predictive models using internal and third-party data, improving onboarding quality and reducing losses.
• Transforming our rule engine: Evolve our static rule engine into a dynamic and conditional graph-based rule engine, enabling more intelligent and adaptable rule management.
• Develop and implement fingerprinting and geographic tracking solutions to improve risk assessment.
• Leading the adoption of new technologies: Drive the adoption of technologies like Databricks and Data Catalogue in the team.
• Data modeling and advanced analytics: Analyze large volumes of transactional, user behavior, and demographic data.
• Mentorship and technical leadership: Guide and mentor team members.
• Defining success metrics: Establish clear and relevant metrics.

• Demonstrable experience in building and implementing machine learning models.
• Deep knowledge of classification, regression, and clustering algorithms.
• Strong programming skills in Python, SQL, and Spark.
• Experience with platforms like Databricks, AWS and Azure.
• Knowledge of relational databases (PostgreSQL) and messaging tools (Kafka, SQS).
• Experience in developing and implementing real-time scoring.
• Ability to communicate complex ideas clearly and concisely.
• Analytical mindset and results-oriented.
• Passion for innovation and experimentation.
• Knowledge of data modeling principles.
• Strong mathematical skills and ability to optimize complex problems.

• Experience with graph-based rule engines.
• Knowledge of fingerprinting and geographic tracking techniques.
• Expertise in MLOPs

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