Quantitative Developer Internship - 2027
Dime Line Trading
Salary undisclosed
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Description
- Contribute to the research, design, and implementation of predictive statistical and machine learning models across prediction markets and exchange venues
- Prototype and backtest models, monitor performance, and assist with optimizations.
- Contribute to key feature development for model efficiency
- Develop and maintain Python codebases in a Linux environment.
- Help to design and implement new pricing models and frameworks
- Support data pipeline and SQL database interactions for real-time models.
- Assist in improving trading systems and operational tools.
- Gain exposure to multiple sports, quantitative disciplines, and production engineering.
- Other duties as assigned.
Skills you’ll need:
- Proficiency in Python (experience in R or other languages a plus).
- Strong interest in statistical modeling, machine learning, or predictive analytics.
- Familiarity with Linux and SQL databases.
- Ability to work in a fast-paced environment and manage multiple tasks.
- Interest in sports and sports analytics / sabermetrics.
- Strong problem-solving and communication skills.
- Predictable and reliable availability
It’s great to see:
- Coursework in statistics, optimization, computer science, or related fields.
- Prior internship or project experience in trading, quantitative research, or software engineering.
- Exposure to object-oriented development, real-time systems, or algorithmic trading models.
- Experience with sports gambling, fantasy sports, or predictive analytics applied to sports.
About this role
Dime Line Trading is looking for a Quantitative Developer Intern to spend 10 weeks working on predictive models and trading systems in their Chicago office. You'd contribute to research and implementation across prediction markets and exchange venues, writing Python code in a Linux environment while prototyping, backtesting, and optimizing statistical and machine learning models. The role also involves SQL database work, feature development for model efficiency, and exposure to pricing frameworks and trading infrastructure.
This internship suits someone with solid Python skills, a genuine interest in statistical modeling or machine learning, and comfort working in Linux and SQL. A background in statistics, computer science, or related coursework is valuable, as is any prior experience in quantitative research, trading, or software engineering. The role has a sports analytics angle—interest in sports, sabermetrics, or sports gambling experience is explicitly encouraged, though not required.
You'd be working in a fast-paced environment where reliability and communication matter as much as technical ability. If you're looking to get real exposure to production systems, model optimization, and how quantitative research actually works in practice, this is a hands-on opportunity across multiple disciplines.
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Pay for this role
The employer didn't post a pay range for this role. That usually means pay is set in negotiation, which favors whoever arrives with numbers. Check ranges on comparable Quantitative Developer Internship - 2027 postings in Chicago, and analyze any offer before you accept it.
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