Frost & Sullivan MetaBrain Early Careers Program – Data Science & Decision Intelligence Internship

Frost & Sullivan; Singapore; On-site; SGD 17,000 - 23,000; Part time

Job summary

Frost & Sullivan invites applications for an AI/data science internship to support MetaBrain. You will work with industry researchers and engineers on building decision-intelligence software and reusable analytics services.

Open to postgraduate students, graduates, or early-career professionals with up to two years of experience. Six-month duration, possible extension to twelve months; paid stipend; full-time conversion not guaranteed.

Qualifications

• When pursuing or holding a Master’s/PhD in AI, data science, statistics, econometrics, applied math, OR, CS with substantive AI/ML coursework or research.
• Strong Python or R, SQL, probability, statistics and model validation.
• A reproducible project showing data preparation, a baseline and defensible evaluation.

Responsibilities

• Build reliable analytical datasets with authorized market, primary-research and enterprise data.
• Develop decision models for forecasting, ranking, or optimization and explain business meaning of targets.
• Test uncertainty and value with held-out or time-based validation, and perform sensitivity analysis.
• Operationalize analysis with reproducible code, data tests, and model interfaces; integrate with MetaBrain workflows.

Skills

Python/R

SQL

Statistics

Model validation

Time-series analysis

Probabilistic modelling

Optimization

Causal inference

Experimental design

Economic data

Education

Master's in AI

Master's in data science

Master's in statistics

PhD in related field

Applied mathematics

Operations research

Computer science

Tools

scikit-learn

TensorFlow

PyTorch

Git

R

Job description

Launch Your Career with Frost & Sullivan

At Frost & Sullivan, we believe that the future belongs to curious minds, innovative thinkers, and problem-solvers who are eager to make an impact. We are inviting applications from postgraduate students, recent graduates, and early-career professionals with up to two years of experience to join our growing global teams across various business, technology, research, consulting, AI, data, and corporate functions.

The Opportunity

Frost & Sullivan is looking for intern roles supporting MetaBrain. The work combines applied AI, business understanding, structured knowledge, quantitative models and trustworthy engineering to transform research and advisory into reusable software-enabled services. Build more than a demonstration. Work with industry researchers, advisors and engineers to turn AI capability into tested decision-intelligence software that enterprises can use.

Role Overview

Show how your technical work supports a business problem. Research, consulting or advisory experience is preferred but not mandatory. Academic projects, thesis and reproducible research implementations are valid evidence; internships do not require prior full-time employment.

Develop the quantitative models and data pipelines behind continuously updated advisory software. Combine rigorous statistical methods with a clear understanding of how enterprises prioritize growth opportunities and test alternatives.

Proposed engagement

Stipend: Yes, paid internship.

Duration: Preferably six months, possibility of an extension up to 12 months based on performance and where academic arrangements and work authorization permits are in place.

Full-time Conversion: Depends on assessed performance, a suitable vacancy and eligibility; it is not guaranteed.

Essential Requirements

Currently pursuing or holding a Master's or PhD in AI, data science, statistics, econometrics, applied mathematics, operations research, computer science or a related field with substantive AI/ML coursework or research. Strong Python or R, SQL, probability, statistics and model validation. A reproducible project showing data preparation, a baseline and defensible evaluation.

Preferred: Time-series analysis, probabilistic modelling, optimization, causal inference, experimental design, survey methods or economic/market data. Familiarity with ML frameworks and version control is useful; candidates need depth in relevant methods rather than every technique.

Key responsibilities

• Build reliable analytical datasets: Prepare authorized market, primary-research and enterprise data. Align time, geography, currency and business definitions; document transformations, missingness, sampling limitations and source lineage.
• Develop decision models: Compare suitable approaches for forecasting, segmentation, ranking, opportunity scoring or optimization. Establish simple baselines before complex methods; explain the business meaning of targets, features and objective functions.
• Test uncertainty and business value: Use appropriate held-out/time-based validation, sensitivity analysis and uncertainty estimates. Distinguish correlation, prediction and causality; avoid leakage and use explainability proportionate to the decision risk.
• Operationalize the analysis: Create reproducible code, data tests and documented model interfaces. Build scenario outputs, drift/quality monitoring and visual explanations; integrate approved models with MetaBrain workflows through engineering review.