Global Macro Quant Researcher - Systematic Equities & ML

Quant Blueprint LLC; Baar; Vor Ort; CHF 90.000 - 120.000; Vollzeit

Zusammenfassung

Quant Blueprint LLC is seeking a Quantitative Researcher specialized in Systematic Equities to develop trading strategies and optimize analytical models. This role requires proficiency in Python and expertise in data science tools. Candidates should have a Bachelor's or Master's degree in a relevant STEM field and at least 3 years of experience in systematic trading environments.

Responsibilities include working with large financial datasets, implementing scalable machine learning frameworks, and collaborating with cross-functional teams to drive data-centered insights and performance. A strong intuition for data prediction and a critical thinking mindset is essential.

Qualifikationen

• 3+ years of experience in a systematic trading environment focusing on equities.
• Experience manipulating data with multiple vendor data sets.
• Theoretical understanding of Machine Learning with 2-3 years of hands-on experience.

Aufgaben

• Develop systematic trading strategies with a focus on idea generation, data analysis, and model implementation.
• Analyze large financial datasets using statistical learning techniques.
• Optimize code for large-scale work.

Kenntnisse

Python

Data science tools (Jupyter, pandas, numpy, sklearn)

Statistical analysis

Machine learning

Problem-solving skills

Communication skills

Ausbildung

Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or related STEM field

Tools

KDB/Q

Jobbeschreibung

Quant Blueprint LLC is seeking a Quantitative Researcher specialized in Systematic Equities to develop trading strategies and optimize analytical models. This role requires proficiency in Python and expertise in data science tools. Candidates should have a Bachelor's or Master's degree in a relevant STEM field and at least 3 years of experience in systematic trading environments.

Responsibilities include working with large financial datasets, implementing scalable machine learning frameworks, and collaborating with cross-functional teams to drive data-centered insights and performance. A strong intuition for data prediction and a critical thinking mindset is essential.