Data Scientist

TECH AALTO PTE. LTD.; Singapore; On-site; SGD 70,000 - 140,000; Full time

Job summary

TECH AALTO PTE. LTD. seeks a data science professional to translate business needs into analytical solutions. You will build and validate predictive models for fraud and risk, work with large datasets, and develop dashboards to monitor performance.

Expect exposure to MLOps, production deployment, data quality and lineage, plus tools like Spark, PySpark and AWS Redshift. Singapore-based engagement preferred.

Qualifications

• Degree in Data Science, Statistics, Mathematics, CS, Engineering, Economics or related quantitative discipline.
• 3-5 years of hands-on data science, analytics, model validation or fraud/risk analytics experience.
• Strong hands-on proficiency in Python and SQL for data extraction, transformation and exploration.

Responsibilities

• Develop, validate or enhance predictive and risk models for fraud/detection.
• Translate business needs into analytical specifications and model logic.
• Work with large datasets, assess data quality and document assumptions.
• Design production model-monitoring approaches for drift and alerts.
• Build analytical dashboards using Tableau or equivalent.

Skills

Python

SQL

Data analysis

Predictive modelling

Fraud detection

Anomaly detection

Model validation

Dashboarding

MLOps

Spark

PySpark

AWS Redshift

Data quality

Data lineage

Education

Degree in Data Science or related quantitative field

Tools

Tableau

AWS Glue

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.