全职 Data Scientist 工作, 薪水 up to SGD 7,000, TECH AALTO PTE. LTD. Islandwide (Singapore) 公司招聘中 - Ricebowl

Job Description

• Education: Degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics or a related quantitative discipline. 
• Experience: 3–5 years of hands-on experience in data science, advanced analytics, model validation, fraud/risk analytics or programme analytics. 

Technical & Professional Competencies 

• Strong hands-on proficiency in Python and SQL for data extraction, transformation, exploratory analysis, with experience building reproducible analytical workflows. 
• Hands-on experience developing, validating or enhancing predictive, risk-scoring, fraud-detection or anomaly-detection models, including feature development, back-testing, threshold calibration and performance evaluation using measures such as precision, recall and related trade-offs. 
• Experience translating business, policy or operational requirements into analytical specifications, model logic, indicators, rules or measurable risk hypotheses. 
• Experience working with complex, large-scale datasets, including assessing data quality, tracing data lineage, investigating anomalies and documenting analytical assumptions. 

• Experience handling the technical challenges to fraud or risk modelling, including imbalanced data and delayed, incomplete or evolving outcome labels. 
• Experience designing or implementing production model-monitoring approaches, including data drift, concept drift and alert thresholds. 
• Experience building analytical dashboards using Tableau or an equivalent platform. 
• Experience with CI/CD, MLOps controls or the operational deployment of analytical models.
• Experience with Spark or PySpark and enterprise data platforms, particularly AWS Redshift and AWS Glue. 
• Experience with network or graph analytics to identify related entities or coordinated patterns. 
• Experience working with workforce, training, grants, claims or regulatory datasets. 
• Prior experience in Singapore public-sector engagements or familiarity with government data-classification requirements

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