as a data scientist at prefr, you will apply your creative problem-solving and analytical skills to design and deploy high-impact machine learning models across multiple business functions. you will be responsible for: 

• design, validate, and productionize advanced machine learning and deep learning models to generate actionable insights for strategic business decisions. focus areas include credit risk prediction, propensity modeling, fraud detection, collection efficiency improvement, and other finance-related applications.

• optimize and tune machine learning algorithms for performance and scalability, ensuring seamless integration with production pipelines and robustness in real-world environments.

• develop and maintain monitoring frameworks to track model performance over time, detect data or concept drift, and provide timely, actionable feedback for retraining or recalibration as needed.

• analyze and interpret large, complex datasets from distributed databases to generate and provide valuable actionable insights to stakeholders using big data technologies like scala-spark/pyspark.

• drive continuous improvement by exploring, researching, and implementing innovative modeling techniques and algorithms.

• stay up-to-date with advancements in ml/ai and proactively apply new techniques to improve model performance or uncover new opportunities.

• as part of our long-term vision, contribute to building agentic systems that automate key parts of the data science pipeline from feature engineering and model selection to monitoring and reporting, enabling faster experimentation and decision-making.