CY
CygnifyData Scientist – AI Fintech
LocationSingapore
Work modeon-site
Typefull-time
SeniorityMid
DepartmentCygnify
Company size201–500 people
PostedJul 24, 2026 · 2mo ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
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
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
Familiarity with Generative AI or LLMs is a plus
Skills
Python
SQL
machine learning
NLP
Generative AI
LLMs
Role: Data Scientist - AI Fintech
Location: Singapore
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.
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Collaborate with cross-functional teams to implement models into production systems.
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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.