Data Science (Banking)
Malaysia - Kuala Lumpur
USD 144K-181K (estimate) Senior-level Full Time
Tasks
- Analyze transaction customer and behavioral datasets
- Apply causal inference methodologies
- Automate repeatable analyses
- Build scalable analytical solutions
- Collaborate with product marketing risk fraud and technology teams
- Create executive presentations and performance tracking
- Design and develop dashboards
- Develop and deploy statistical models and machine learning solutions
- Document analytics methodologies code and outputs
- Engineer datasets for predictive modeling
- Lead analytics workstreams across credit card portfolio lifecycle
- Lead knowledge transfer
- Optimize and enhance production code for business processes
- Perform customer segmentation and lifecycle modeling
- Run test and learn experiments using A B testing and control groups
- Translate analytical findings into business recommendations
Perks/Benefits
Skills/Tech-stack
A/B | A/B Testing | Apache Hadoop | Apache Spark | B testing | Causal Inference | Classification | Clustering | Credit Risk | Customer Segmentation | Data Engineering | Fraud analytics | Hive | Machine Learning | Power BI | Propensity Modeling | Python | Regression | SQL | Series analysis | Statistical modeling | Tableau | Time Series | Time Series Analysis | Uplift analysis
Education
Roles
Regions
Countries
States
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