jobs in Ambition

全职 Data Scientist 工作, 薪水, Ambition Federal Territory 公司招聘中 - Ricebowl

Data Scientist

Ambition

Undisclosed

KL City, Federal Territory

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工作地点

  • Kuala Lumpur Federal Territory Malaysia

职位描述

岗位职责

Data Scientist | Credit Card Portfolio Analytics | Kuala Lumpur

If you're a data science professional with a passion for financial analytics, this is a standout opportunity. Join a globally respected payments environment and lead analytical workstreams that deliver real impact across a high-value card portfolio.

Why Apply?

Based in Kuala Lumpur on a 12-month contract, this role places you at the centre of credit card portfolio strategy - from acquisition and activation through to fraud and risk. You'll work alongside senior stakeholders and cross-functional teams, with your insights directly influencing business performance.

The Role

Driving analytics across the full card lifecycle, you'll build models, test hypotheses, and surface insights that matter.

  • Own analytical workstreams spanning acquisition, usage, retention, fraud, and credit risk
  • Build and deploy machine learning and statistical models to uncover portfolio opportunities
  • Design A/B tests and causal inference frameworks to evaluate strategies
  • Develop segmentation, propensity, and uplift models to support portfolio decisions
  • Analyse large-scale transaction datasets to surface actionable insights
  • Create performance dashboards using tools such as Tableau or Power BI
  • Translate findings clearly for both technical and non-technical stakeholders

What We're Looking For

A strong technical foundation paired with the ability to tell compelling data stories.

  • Master's degree or above in Data Science, Statistics, Mathematics, or a related discipline
  • 5-8+ years in data science or advanced analytics, ideally within financial services
  • Experience in credit card analytics, lifecycle modelling, or marketing optimisation
  • Proficiency in SQL, Python, Spark, Hive, or cloud-based analytics platforms
  • Hands-on experience with supervised and unsupervised machine learning techniques
  • Solid grasp of statistical inference, experimental design, and causal methods
  • Confident communicator able to engage senior, non-technical audiences
  • Exposure to fraud, credit risk, or payments analytics is a strong advantage

Ready to drive impact in a high-profile payments environment? Apply now and take the next step in your data science career.

Company Registration Number: *************88 (1048918-T)

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