2026 Summer Internship - Quantitative Strategies (US)

Quant Blueprint LLC; New York (NY); On-site; USD 175,000 - 250,000; Full time

Benefits offered by this job

Gym membership

Free breakfast, lunch, and dinner

Unlimited office snacks

Team outings

Job summary

Quant Blueprint LLC is seeking a Quantitative Researcher to work on autonomous trading agents. The ideal candidate will have a PhD or Master's in a relevant field and strong coding skills in C++ or Python. Collaboration and a passion for analytics are essential.

The role offers a fun work environment with benefits like unlimited snacks, health coverage, and team outings. The salary range is between $175,000 and $250,000, reflecting experience and skill level.

Qualifications

• Demonstrable experience coding in C++ or Python in a Linux environment.
• Experience analyzing large datasets with statistical and machine learning approaches.
• Advanced knowledge of AI, deep learning, and machine learning algorithms.

Responsibilities

• Contribute to the research and development of autonomous trading agents.
• Collaborate with researchers and traders to test and refine trading strategies.

Skills

C++ coding

Python coding

Statistical analysis

Machine learning expertise

Deep learning knowledge

Time-series analysis

Education

PhD or Master's Degree in Computer Science, Statistics, Mathematics, Electrical Engineering, Physics

Tools

Linux environment

Python (numpy/scipy stack)

Job description

As a Quantitative Researcher at Vatic, you will contribute to the research and development of fully autonomous trading agents with some of the brightest researchers, traders, and technologists in the world. You will apply cutting edge machine learning and artificial intelligence algorithms to vast amounts of market data to discover and capitalize on trading opportunities.

We are selectively considering Researchers who have demonstrated the ability to generate impactful research in their academic and professional pursuits. We foster an open and academic environment, where collaboration is the key to our success. Drawing from our collective backgrounds in Computer Science, Mathematics, Statistics, and Physics, we apply rigorous analytics to test hypotheses derived from years of successful quantitative trading. We are passionate about hiring the best and the brightest, empowering them with the tools and mentorship needed to be successful.

If you possess the following, we would love to explore what is available for you with our team:

• Earned or will earn a PhD or Master's Degree in Computer Science, Statistics, Mathematics, Electrical Engineering, Physics, or related fields
• Demonstrable experience coding in C++ or Python in a Linux environment
• Have experience analyzing large datasets with rigorous statistical and machine learning approaches, including classification, clustering, and regression
• In depth technical knowledge of AI, deep learning, and machine learning algorithms including strong knowledge of the mathematical underpinnings behind these various methods
• Have innate curiosity for understanding why and how certain techniques work
• Have deep knowledge of time-series analysis
• Advanced knowledge of a high-level language for numerical analysis, Python (numpy/scipy stack) preferred
• Contribution to AI and ML research communities, top-tier peer reviewed publications, publishing/presenting papers at conferences such as NeurIPS, ICML, etc.
• Have interest and enthusiasm for learning about financial markets (previous experience not required)

While we are serious about our work at Vatic, we also promote a fun environment!

You can expect:

• Ping pong and poker games
• Fun team outings
• Unlimited office snacks
• Free breakfast, lunch, and dinner
• Gym membership
• Full health insurance coverage for employees and dependents

*The base salary range for this role is between $175,000 and $250,000. The base salary range does not include any other form of compensation, such as any bonus amounts, or any benefits. Factors that may impact the agreed upon base salary within the range for a particular candidate include years of experience, level of education obtained, skill set, and other factors.*