Quantitative Researcher: ML & Stats for Trading

Kernel Trading Technologies LP; Chicago (IL); Sur place; USD 120 000 - 180 000; Plein temps

Résumé du poste

Kernel Trading Technologies LP invites highly qualified Quantitative Researchers to join our team. You will work with portfolio managers, quantitative developers and technologists to develop and improve our proprietary trading models using data analysis, statistics and machine learning on real-world financial data.

You will analyze large datasets, test models, and communicate complex quantitative concepts to non-technical colleagues while staying current on market conditions and industry trends.

Qualifications

• Advanced degree in a quantitative field.
• Strong programming skills in Python or C++.
• Solid understanding of probability, statistics, and machine learning.
• Knowledge of data structures, algorithms, and numerical methods.
• Ability to communicate complex quantitative concepts to a technical team.

Responsabilités

• Develop, test, and implement quantitative models for trading strategies.
• Analyze large datasets to identify opportunities and improve models.
• Collaborate with developers to implement models in the trading system.
• Conduct market research to stay current on conditions and industry trends.
• Communicate complex quantitative concepts to non-technical stakeholders.

Connaissances

Python

C++

Statistics

Machine Learning

Data Analysis

Communication

Team Collaboration

Formation

Advanced degree in Mathematics/Physics/Statistics/CS/Engineering

Description du poste

Kernel Trading Technologies LP invites highly qualified Quantitative Researchers to join our team. You will work with portfolio managers, quantitative developers and technologists to develop and improve our proprietary trading models using data analysis, statistics and machine learning on real-world financial data.

You will analyze large datasets, test models, and communicate complex quantitative concepts to non-technical colleagues while staying current on market conditions and industry trends.