Data Scientist

Tech Aalto Pte Ltd; Singapore; On-site; SGD 70,000 - 120,000; Full time

Job summary

Tech Aalto Pte Ltd in Singapore is seeking a data science professional with 3–5 years hands-on experience in data science, advanced analytics, and model validation. You will develop and validate predictive and risk-scoring models, and work with fraud/risk analytics to provide actionable insights.

Responsibilities include transforming business requirements into analytical specifications, handling large-scale datasets, and building reproducible workflows using Python and SQL.

Qualifications

• Degree in a quantitative discipline (Data Science, Statistics, Mathematics, CS, Engineering, Economics)
• 3–5 years hands‑on experience in data science, advanced analytics, model validation, fraud/risk analytics or programme analytics.

Skills

Python

SQL

Model development

Fraud/risk analytics

Data analysis

Analytical thinking

Education

Degree in Data Science/Statistics/Mathematics/CS/Engineering/Economics

Tools

Tableau

Spark/PySpark

AWS Redshift

AWS Glue

CI/CD

MLOps

Job description

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