Data Scientist: Classical ML & Gen AI Validation

NCS Pte Ltd; Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

NCS Pte Ltd in Singapore is seeking a Data Scientist to translate business problems into rigorous statistical and ML solutions, building baselines and validating models to support Gen AI initiatives. You’ll work with SMEs, PMs, and AI engineers to ensure measurable outcomes and robust evaluation across engagements.

The role emphasizes statistical rigor, data quality assessment, and collaboration on evaluation design, with opportunities to mentor and contribute to production-grade analytics in a

Qualifications

• 4+ years hand-on experience in statistical modelling / classical machine learning.
• Strong grounding in statistics – hypothesis testing, regression, experimental design, causal inference basics.
• Proficiency in Python (pandas, scikit-learn, statsmodels) and SQL.
• Comfortable working with structured/tabular data at production scale.
• Familiarity with Gen AI concepts (embeddings, RAG, prompting) to collaborate with AI Engineers.

Responsibilities

• Translate business problems into well-defined statistical/ML problems with hypotheses and success metrics.
• Perform exploratory data analysis to understand distributions, correlations, and data quality issues.
• Build and validate classical ML models (regression, classification, clustering, time-series forecasting) as baselines or solutions.
• Apply rigorous validation – train/test/holdout, cross-validation, significance testing to avoid overfitting.
• Collaborate with AI Engineers on evaluation design and feed both classical models and Gen AI/RAG systems.

Skills

Statistical modelling

Classical machine learning

Hypothesis testing

Experiment design

Data analysis

Tools

Python

SQL

Pandas

scikit-learn

statsmodels

Job description

NCS Pte Ltd in Singapore is seeking a Data Scientist to translate business problems into rigorous statistical and ML solutions, building baselines and validating models to support Gen AI initiatives. You’ll work with SMEs, PMs, and AI engineers to ensure measurable outcomes and robust evaluation across engagements.

The role emphasizes statistical rigor, data quality assessment, and collaboration on evaluation design, with opportunities to mentor and contribute to production-grade analytics in a