Senior Research Scientist - Machine Learning

About the Role

We seek a Senior Research Scientist specialized in machine learning to spearhead development of sophisticated models analyzing financial behaviour. The role involves working with extensive behavioural datasets to create models addressing credit risk, repayment forecasting, segmentation, fraud detection, and early warning signals by leveraging advanced sequence modeling, representation learning, and cutting-edge ML techniques.

Responsibilities

• Guide the technical vision for research and modeling initiatives.
• Design, pre-train, and fine-tune models based on sequence and representation learning.
• Utilize transaction, repayment, behavioural, and customer data for model development.
• Create reusable customer representations adaptable across diverse markets and applications.
• Transition models from research phases to production environments and oversee ongoing performance monitoring.
• Stay updated with leading-edge research and incorporate new methods to address practical challenges.
• Collaborate with cross-functional teams including data, product, risk, and engineering departments.
• Mentor fellow scientists to elevate the team's technical expertise.

Requirements

• Master’s degree or PhD in Machine Learning, Computer Science, Statistics, Mathematics, or equivalent disciplines.
• Extensive experience handling sequential, event-level, or time-series data.
• Proficiency with transformer architectures, representation learning, autoregressive, or masked modeling approaches.
• Demonstrated success in pretraining and fine-tuning sequence-based models.
• Strong command of Python programming and SQL querying.
• Familiarity with large-scale data processing platforms including PySpark, Databricks, Snowflake, or BigQuery.
• Experience managing and analyzing complex, real-world datasets.
• Background in credit risk modeling, financial machine learning, fraud detection, alternative data scoring, multi-modal data usage, or model governance.