Quantitative Developer for New Graduates
$44.5k - $64.5kInternship
Dime Line Trading
Salary: $44,500 - 64,500 per year Requirements:
- Proficiency in Python; experience with R or another programming language is a plus.
- Strong interest in statistical modeling, machine learning, or predictive analytics.
- Working knowledge of Linux and SQL databases.
- Ability to thrive in a fast-paced setting and juggle multiple priorities.
- Genuine interest in sports and sports analytics or sabermetrics.
- Strong analytical problem-solving abilities and clear communication skills.
- Reliable and predictable availability.
- Relevant coursework in statistics, optimization, computer science, or a related discipline is a plus.
- Prior internship or project experience in trading, quantitative research, or software engineering is a plus.
- Exposure to object-oriented development, real-time systems, or algorithmic trading models is a plus.
- Experience with sports betting, fantasy sports, or sports-focused predictive analytics is a plus.
- Contribute to the research, design, and implementation of predictive statistical and machine learning models across prediction markets and exchange venues.
- Build prototypes, backtest models, monitor performance, and support optimization efforts.
- Help develop key features that improve model efficiency.
- Develop and maintain Python codebases in a Linux environment.
- Assist in designing and implementing new pricing models and frameworks.
- Support data pipelines and SQL database interactions for real-time models.
- Help improve trading systems and operational tools.
- Gain exposure to multiple sports, quantitative disciplines, and production engineering.
- Perform other assigned duties as needed.
- Support
- Linux
- Machine Learning
- Python
- SQL
More:
We are looking for someone to join our team and work on predictive modeling, pricing frameworks, and trading systems across prediction markets and exchange venues. This role offers hands-on exposure to Python development, Linux, SQL, machine learning, sports analytics, and production engineering, with opportunities to contribute across a fast-paced, quantitative environment.
last updated 33 week of 2026
Vacancy posted 1 day ago
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