Data Science Intern: Investment Analytics & Insights

Viking Global Investors; New York (NY); On-site; USD 175,000 - 250,000; Full time

Benefits offered by this job

Discretionary bonus

Medical and dental premiums covered 0

Paid lunches

Job summary

Viking Global Investors in New York, NY seeks a Data Science Intern for a 10-week summer program. Work with Data Science, Investment Analysts, and Data Engineers to analyze and extend Viking’s data assets and generate actionable insights for the investment process.

Candidates should be pursuing a Master’s or PhD (3rd year+), have strong Python and statistics background, and knowledge of SQL, BI tools (Tableau), cloud tech, and modern LLM tooling.

Qualifications

• Pursuing a Master’s/PhD (3rd year+) in quantitative field.
• Strong communication and ability to convey complex ideas to non-technical audiences.
• Independence to carry out a research project with partial supervision.

Responsibilities

• Build and deliver predictive analytics on companies, sectors, and macro trends.
• Translate data analysis into actionable investment insights for the team.
• Develop methodologies to identify investment opportunities in private companies.
• Identify and evaluate new data sources.
• Streamline data life cycle and processes.
• Test new technologies to enhance the big data platform.
• Create centralized analyses and processes.
• Share insights across the firm.

Skills

Strong communication

Independent research

Analytical rigor

Passion for research

Commitment to excellence

Education

Master’s degree or PhD (3rd year+ in Data Science, Economics, Finance, Statistics, OR)

Tools

Python

SQL

Tableau

Cloud technologies

LLM tooling (Claude Code, Codex)

Job description

Viking Global Investors in New York, NY seeks a Data Science Intern for a 10-week summer program. Work with Data Science, Investment Analysts, and Data Engineers to analyze and extend Viking’s data assets and generate actionable insights for the investment process.

Candidates should be pursuing a Master’s or PhD (3rd year+), have strong Python and statistics background, and knowledge of SQL, BI tools (Tableau), cloud tech, and modern LLM tooling.