Senior Fintech Data Scientist: ML for Credit & Fraud

YTL Digital Bank Berhad (Registration No. 202201037182 (1482879-P); Malaysia; On-site; MYR 180,000 - 240,000; Full time

Job summary

Ryt Bank is seeking a Senior Data Scientist to drive product innovation through advanced analytics, experimentation, and ML. You will own the full lifecycle—from experiments to production deployment—within fintech product teams, delivering measurable business impact across fraud detection, credit decisioning, and user experience optimization.

You will design and deploy scoring systems, forecast models, and personalized recommendations, while mentoring junior data scientists and promoting

Qualifications

• 5+ years of experience in data science, with fintech exposure.
• Expert-level proficiency in Python and ML frameworks (Tensorflow, PyTorch, XGBoost).
• Strong foundation in statistics, hypothesis testing, and experimental design.
• Production experience with SQL and large-scale datasets (terabytes+).
• Proven track record deploying ML pipelines in production.

Responsibilities

• Design and implement advanced ML models for credit risk, fraud detection, and CLV prediction.
• Partner with product teams to translate business challenges into data science solutions.
• Build predictive models for churn, acquisition, and engagement strategies.
• Develop scoring systems for loan decisioning and transaction monitoring.

Skills

Python

Statistical methods

Experiment design

Stakeholder communication

Team leadership

Product mindset

Agile

Education

Bachelor's degree in a relevant field

Tools

TensorFlow

PyTorch

XGBoost

SQL

MLflow

SageMaker

Job description

Ryt Bank is seeking a Senior Data Scientist to drive product innovation through advanced analytics, experimentation, and ML. You will own the full lifecycle—from experiments to production deployment—within fintech product teams, delivering measurable business impact across fraud detection, credit decisioning, and user experience optimization.

You will design and deploy scoring systems, forecast models, and personalized recommendations, while mentoring junior data scientists and promoting