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Frost & Sullivan invites postgraduate students, recent graduates, and early-career professionals to apply for intern roles supporting MetaBrain. The position blends applied AI with business insight, data pipelines, and tested decision-intelligence software, aimed at transforming research into reusable software-enabled services.
Ideal candidates are pursuing or holding a Master’s/PhD in AI/data science or related fields, with strong Python or R, SQL, probability, statistics and model validation
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.
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.
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.
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.
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.