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Quantitative Researcher | Prediction Markets

at Susquehanna

Back to all Data Science / AI / ML jobs
Susquehanna logo
Proprietary Trading

Quantitative Researcher | Prediction Markets

at Susquehanna

Mid LevelNo visa sponsorshipData Science/AI/ML

Posted 4 hours ago

No clicks

Compensation
Not specified

Currency: Not specified

City
Not specified
Country
Not specified

Quantitative Researcher on the Prediction Markets team responsible for designing, analyzing, and optimizing models and strategies for prediction markets. The role involves statistical forecasting, probability calibration, market microstructure analysis, and working with large datasets to inform trading and execution improvements while collaborating with traders and technologists.

JOB DESCRIPTION
Overview

At Susquehanna, our Quantitative Researchers apply mathematics, statistics, and programming to solve complex problems in financial markets. As a Quantitative Researcher on our Prediction Markets team, you will focus on designing, analyzing, and optimizing strategies for prediction markets—leveraging advanced quantitative techniques to model probabilities, calibrate forecasts, and improve trading performance. This role combines rigorous research with real-time impact, working alongside traders and technologists to innovate in a rapidly evolving space.

What You’ll Do

  • Develop and refine models for pricing and liquidity in prediction markets.
  • Analyze trading and strategy data to identify optimization opportunities.
  • Collaborate with modelers to implement mathematical frameworks for market-making and risk management.
  • Study market microstructure to uncover fair-agnostic optimizations and execution improvements.
  • Build statistical forecasting models to enhance probability calibration and decision-making.
  • Work with large datasets to extract actionable insights and validate hypotheses.

What we're looking for
  • Master’s or PhD in a STEM field (Mathematics, Statistics, Physics, Computer Science, Electrical Engineering, Operations Research, or related discipline).
  • Strong theoretical foundation in probability and statistics.
  • Experience with large-scale data analysis and statistical modeling.
  • Proficiency in Python and scientific libraries (NumPy, Pandas); familiarity with object-oriented programming.
  • Ability to think creatively and challenge conventional approaches.
  • Familiarity with trading concepts; prediction market experience is a plus.
  • Previous finance experience is not required, but a passion for solving real-time market problems is essential.

What You Can Expect From Us

  • A collaborative, non-hierarchical environment where ideas drive impact.
  • Access to industry-leading technology and resources from one of the largest proprietary trading firms.
  • Extensive training and mentorship programs led by top performers.
  • Opportunities to work on complex technical challenges with immediate influence on trading decisions.
  • A balanced culture that values intellectual rigor and work-life harmony.

#LI-WD1

Quantitative Researcher | Prediction Markets

at Susquehanna

Back to all Data Science / AI / ML jobs
Susquehanna logo
Proprietary Trading

Quantitative Researcher | Prediction Markets

at Susquehanna

Mid LevelNo visa sponsorshipData Science/AI/ML

Posted 4 hours ago

No clicks

Compensation
Not specified

Currency: Not specified

City
Not specified
Country
Not specified

Quantitative Researcher on the Prediction Markets team responsible for designing, analyzing, and optimizing models and strategies for prediction markets. The role involves statistical forecasting, probability calibration, market microstructure analysis, and working with large datasets to inform trading and execution improvements while collaborating with traders and technologists.

JOB DESCRIPTION
Overview

At Susquehanna, our Quantitative Researchers apply mathematics, statistics, and programming to solve complex problems in financial markets. As a Quantitative Researcher on our Prediction Markets team, you will focus on designing, analyzing, and optimizing strategies for prediction markets—leveraging advanced quantitative techniques to model probabilities, calibrate forecasts, and improve trading performance. This role combines rigorous research with real-time impact, working alongside traders and technologists to innovate in a rapidly evolving space.

What You’ll Do

  • Develop and refine models for pricing and liquidity in prediction markets.
  • Analyze trading and strategy data to identify optimization opportunities.
  • Collaborate with modelers to implement mathematical frameworks for market-making and risk management.
  • Study market microstructure to uncover fair-agnostic optimizations and execution improvements.
  • Build statistical forecasting models to enhance probability calibration and decision-making.
  • Work with large datasets to extract actionable insights and validate hypotheses.

What we're looking for
  • Master’s or PhD in a STEM field (Mathematics, Statistics, Physics, Computer Science, Electrical Engineering, Operations Research, or related discipline).
  • Strong theoretical foundation in probability and statistics.
  • Experience with large-scale data analysis and statistical modeling.
  • Proficiency in Python and scientific libraries (NumPy, Pandas); familiarity with object-oriented programming.
  • Ability to think creatively and challenge conventional approaches.
  • Familiarity with trading concepts; prediction market experience is a plus.
  • Previous finance experience is not required, but a passion for solving real-time market problems is essential.

What You Can Expect From Us

  • A collaborative, non-hierarchical environment where ideas drive impact.
  • Access to industry-leading technology and resources from one of the largest proprietary trading firms.
  • Extensive training and mentorship programs led by top performers.
  • Opportunities to work on complex technical challenges with immediate influence on trading decisions.
  • A balanced culture that values intellectual rigor and work-life harmony.

#LI-WD1

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