Sr. Data Scientist - AI Fintech

CYGNIFY PTE. LTD.; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

CYGNIFY PTE. LTD. in Singapore is seeking a Data Scientist with expertise in banking models, fraud analytics, and machine learning. You will design predictive models, detect fraud patterns, and collaborate with Risk, Product, and Engineering teams to deliver data-driven solutions.

The role focuses on building and deploying models for credit risk, fraud detection, and payments, while ensuring regulatory compliance and robust monitoring in production environments.

Qualifications

• Bachelor’s or Master’s degree in Data Science, Statistics, CS, or related field.
• Proven experience in data science, preferably within banking, fintech, or fraud analytics.
• Strong proficiency in Python, SQL, and machine learning techniques.
• Hands-on experience with NLP techniques.
• Familiarity with Generative AI or LLMs is a plus.
• Solid understanding of banking products, fraud schemes, and risk modeling techniques.
• Hands-on experience with supervised and unsupervised machine learning, applied statistics, and AI methods.

Responsibilities

• Build and deploy machine learning models for credit risk, payments, and fraud detection.
• Analyze transactional data to identify fraud patterns and emerging risks.
• Perform feature engineering, model training, validation, and monitoring.
• Collaborate with cross-functional teams to implement models into production systems.
• Ensure all models meet regulatory and compliance standards.

Skills

Python

SQL

ML techniques

NLP

Education

Bachelor’s or Master’s degree in Data Science, Statistics, CS

Tools

Pandas

scikit-learn

Regulatory tooling

Job description

We are partnering with a leading AI Fintech seeking a Data Scientist with expertise in banking models, fraud analytics, and machine learning. You will design predictive models, detect fraud patterns, and collaborate with Risk,Product, and Engineering teams to deliver data-driven solutions.

Responsibilities:

• Build and deploy machine learning models for credit risk, payments, and fraud detection.
• Analyze transactional data to identify fraud patterns and emerging risks.
• Perform feature engineering, model training, validation, and monitoring.
• Collaborate with cross-functional teams to implement models into production systems.
• Ensure all models meet regulatory and compliance standards.

Requirements:

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or related field.
• Proven experience in data science, preferably within banking, fintech, or fraud analytics.
• Strong proficiency in Python, SQL, and machine learning techniques.
• Hands-on experience with NLP techniques.
• Familiarity with Generative AI or LLMs is a plus.
• Solid understanding of banking products, fraud schemes, and risk modeling techniques.
• Hands-on experience with supervised and unsupervised machine learning, applied statistics, and AI methods.