Quantic – Quantitative Developer Intern (Summer 2027)

Walleye Capital Internships•Boston, MA

22h•$20,000•Onsite

About The Position

Walleye Capital is seeking highly technical and analytically-minded Quantitative Developer Interns to work in the rapidly growing Quantic team based out of Boston. Quantic is Walleye’s principal quantitative investment business, established in 2016 as one of its core investment strategies. Quantic has subsequently evolved into one of the most successful trading teams in the industry. We are a tight-knit, collaborative, and intellectually rigorous group of scientists, engineers, and traders leveraging advanced statistical modeling techniques to identify and capitalize on profitable trading opportunities in global equities, options, and futures. This role offers the opportunity to engage directly with cutting-edge data analysis, portfolio optimization, platform development, and operation of fully automated trading systems. You will join a team where your creativity, initiative, and teamwork will make direct impacts on trading profits for our investors. We invite developers with a proven record of innovation and achievement in their fields to apply. As a Quantic Intern, you’ll work directly with experienced team members on meaningful projects that impact trading strategies and operations. You’ll have the opportunity to work on high-impact initiatives and develop your skills in a dynamic setting where innovation, teamwork, and talent drive success. We are seeking students with strong technical backgrounds (e.g., mathematics, statistics, computer science, or engineering), demonstrated initiative, and an interest in quantitative trading and research. Successful interns are curious, collaborative, and eager to tackle complex problems in a fast-paced, supportive environment. The internship is 10 weeks in length and will take place in Boston from June to August 2027.

Requirements

Pursuing an undergraduate or advanced degree in computer science, engineering, statistics, mathematics, or a related field, with an expected graduation date between December 2027 and June 2028.
Exhibit strong quantitative and analytical skills, including proficiency in a scripting language (Python/BasH/Perl) and experience in UNIX/Linux/BSD environments.
Demonstrate familiarity with popular machine learning/deep learning/statistical packages (such as scikit-learn, TensorFlow, PyTorch, etc.).
Are self-starters who enjoy digging into complex, open-ended problems and can work both independently and collaboratively with a team.
Exhibit a genuine interest in financial markets, systematic investing, AI/LLM application, and using technology in dynamic, data-rich environments.
Showcase creativity and enthusiasm for leveraging AI tools to enhance productivity, improve processes, and generate investment alpha.
Thrive in a collaborative culture that values intellectual humility, creativity, and continuous learning.

Responsibilities

Develop and deploy quantitative infrastructure supporting alpha generation, portfolio construction, and algorithmic trading.
Design and manage data pipelines; triage data integrity quality – improving reliability, consistency, and traceability of financial datasets.
Partner with traders and researchers to develop and iterate on proprietary trading strategies and alphas.
Build reporting and analysis tools for strategy risk, trade cost and execution using data from a proprietary columnar database.
Utilize coding skills and leverage AI tools to oversee and improve automated trading systems.