About Applied Academics
• Applied Academics is a scientific research firm that has pioneered quantitative methods for predicting the future
performance of investment managers. Historically, the industry’s reliance on backward-looking analyses has failed to help
investors reliably identify skilled managers and generate alpha. Our groundbreaking statistical framework, Goose,
separates skill from luck to produce precise estimates of managers’ future performance.
• Developed from first principles by our team of world-class researchers, Goose’s accuracy was first validated through
deployment at one of the leading multi-manager hedge funds. Since then, our scientific approach has been adopted by
some of the world’s largest institutional investors, including government pensions and sovereign wealth funds,
transforming how billions of dollars are invested globally. Clients partner with us as a quantitative “manager of managers”
to construct portfolios of skilled managers, and measure our value by the portfolios’ performance.
• At Applied Academics, our research team forms the core of the firm’s “front office” that drives investment decisions and
our performance-focused business model. Their primary responsibility is to maximize the performance of our clients’
portfolios. The team is dedicated to continually improving Goose through a highly collaborative and disciplined research
process. As an independent firm with no external stakeholders, our researchers have the rare privilege of never having to
sacrifice scientific truths and long-term value creation for the convenience of short-term business gains.
Position Overview
• We are seeking quantitative analyst interns to join our research team and contribute to the continued evolution of Goose.
You will work with large datasets and apply Goose’s advanced statistical framework to evaluate investment managers.
You’ll gain hands-on experience in data analysis, model development, and supporting decision-making on our portfolios.
• We are a close-knit team of dedicated researchers with a flat organizational structure that promotes open
communication. Everyone, including the CEO, is accessible, ensuring that questions or concerns are addressed quickly.
There are no silos within or across teams, and our efficient communication fosters rapid problem-solving and innovation.
Our workplace is free of office politics; we support one another and are united in achieving shared goals.
• You will start with a guided onboarding and training curriculum (tools, data sources, research workflow) paired with close
mentorship. From there, you will rotate through selected projects that connect the full stack and offer broad, hands-on
exposure to our framework. We are committed to fostering your professional growth through thoughtful mentorship and
ensuring you have a rewarding, impactful career at Applied Academics.
• If you are passionate about finance, data analysis, and quantitative research—and eager to learn how we identify and
combine investment managers to create consistent, high-performance portfolios—we’d love to hear from you. This is a
unique opportunity to work in a fast-paced, research-driven environment where your contributions will have a meaningful
impact.
• This is a full-time summer internship based in New York City, requiring in-office collaboration five days a week. The
program typically runs in the summer, while fall/spring terms are also available for candidates who can commit to fulltime hours.
Key Responsibilities
• Support Investment Decisions: Work alongside senior researchers to contribute to manager selection and portfolio
construction decisions. Analyze large datasets to understand investment managers and uncover insights. Produce
dashboards and reports to present findings in an understandable and actionable format.
• Next-Gen Goose Research: Research new datasets, tools, and methodologies to enhance Goose’s manager evaluation
and portfolio construction framework. Develop and implement models for data analysis, performance evaluation, and risk
management using tools like Python/C++.
• Data Integration & Automation: Use state of art data architecture to help build and maintain a scalable data pipeline to
gather, clean and process large datasets. Support the optimization and automation of data ingestion, transformation, and
integration for efficient workflows and accurate analysis.
Qualifications and Characteristics
Education:
• Bachelor’s, Master’s, or PhD in Computer Science, Data Science, Finance, Economics, Mathematics, Engineering, or a
related field (or equivalent work experience).
Skills & Experience:
• Proficiency in Python for data manipulation, statistical modeling, and automation.
• Strong knowledge of data structures, algorithms, and database management systems.
• Experience with data engineering and building data pipelines using tools like Pandas, NumPy, SQL, or similar technologies.
• Strong analytical skills with the ability to work with large datasets and extract meaningful insights.
• Familiarity with financial data platforms (e.g., Refinitiv, Bloomberg, FactSet) and APIs is a plus.
Statistical & Finance Skills:
• Strong foundation in statistics and quantitative analysis techniques (e.g., regression analysis, hypothesis testing).
• Knowledge of financial concepts (e.g., risk management, performance evaluation) or a keen interest in learning advanced
financial topics is essential.
Soft Skills:
• High attention to detail and the ability to ensure accuracy and consistency across data sources and outputs.
• Problem-solving mindset with the ability to develop creative solutions to complex data challenges.
• Strong collaboration skills and the ability to work effectively in a small, dynamic team.
• Excellent written and verbal communication skills for conveying data findings clearly.
• Strong intellectual curiosity and integrity to deliver high-quality research.
Compensation & Benefits
• Salary: $10,000 per month.
• High-performing interns may receive a full-time offer at the conclusion of the internship.
• CPT/OPT support is available for international students.
How to Apply
• Please submit your resume and a brief cover letter to recruiting@appliedacademics.com explaining why you’re interested
in the role and how your skills and experiences align with our team’s needs. We look forward to hearing from you!
