Quantitative Researcher - Metals

Qube Research and Technologies Switzerland AG; Genf; Vor Ort; CHF 140.000 - 200.000; Vollzeit

Zusammenfassung

Qube Research and Technologies Switzerland AG is seeking a Quantitative Researcher - Metals to combine fundamental and quantitative research, translating supply and demand analysis into actionable trading signals, alongside modelling, dashboard development and trade execution.

You will work with large datasets to identify statistical patterns, share results with researchers, implement signals on the global platform and monitor model performance while leading the full cycle from signal generation

Qualifikationen

• Advanced degree in a quantitative field.
• Strong knowledge in statistics, machine learning, NLP or AI.
• Experience coding in Python, R, Matlab, C++, or C#.
• Ability to work autonomously in a fast-paced, global team.
• Experience analyzing large datasets across multiple time frames is a plus.

Aufgaben

• Create high quality predictive signals.
• Identify statistical patterns and opportunities from large datasets.
• Share and discuss results, methodology, datasets and processes with other researchers.
• Implement signals and datasets within the global execution platform.
• Monitor signal behaviour and model performance over time.
• Lead the full strategy research cycle from signal generation to implementation.

Kenntnisse

Quantitative degree

Statistics

Machine learning

NLP/AI

Python

R

Matlab

C++

C#

Dataset exploration

Data analysis

Communication

Autonomy

Ausbildung

Bachelor’s degree from a university of applied sciences or equivalent

Tools

Python

R

Matlab

C++

C#

Jobbeschreibung

Quantitative Researcher - Metals

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.

Your future roleThe role combines fundamental and quantitative research, translating supply & demand analysis into actionable trading opportunities, alongside modelling, dashboard development and trade execution.

Your responsibilities include :Your core objective is to create high quality predictive signals.By leveraging access to large and diversified datasets you will identify statistical patterns and opportunities.Share and discuss research results, methodology, data sets and processes with other researchers.Implement the signals and the relevant datasets within the global execution platform.Monitor signal behaviour and model performance over time.You would lead the full strategy research cycle from signal generation to implementation.

Your present skillsetAdvanced degree in a quantitative field such as data science, statistics, mathematics, physics or engineering.Strong knowledge in statistics, machine learning, NLP or AI techniques.Knowledge of major Asian languages desirable.Capacity to multi-task in a fast-paced environment while keeping strong attention to detail.Coding skills required in at least one leading programming language (Python, R, Matlab and /or C++, C#).Experience in exploring large datasets across multiple time frames is a plus.Intellectual curiosity to explore new data sets, solve complex problems, drive innovative processes and connect the dots between multiple fields.Capacity to work with autonomy within a collegial and collaborative environment.Strong capacity to communicate with technologists, data scientists and traders across the globe.Proven track record in delivering successful systematic strategies.

• Work location 1204 Genève (GE)
• Additional information on the place of work Cours de Rive 10
• Workload 100%
• Employment start Immediately
• Employment duration Permanent

• Work experience More than 1 year
• Education Bachelor’s degree from a university of applied sciences or equivalent

• English Orally : Very good knowledge Written : Very good knowledge

• By email [e-mail]