Data Scientist - Options

Quberesearchandtechnologies; Paris; Sur place; EUR 60 000 - 80 000; Plein temps

Avantages offerts par ce poste

Healthy work-life balance initiatives

Diversity and inclusion programs

Résumé du poste

Quberesearchandtechnologies in Paris is looking for a Data Scientist to support its Options trading streams. You'll work closely with traders and researchers to source high-quality data for systematic trading.

The ideal candidate has over 3 years of experience in data roles, especially with financial market data. Strong Python programming skills and a demonstrated interest in financial markets are essential.

QRT fosters a culture of innovation and offers great work-life balance initiatives.

Qualifications

• 3+ years of experience in a data-focused role, particularly supporting quantitative research or trading.
• Exposure to options, derivatives, or volatility data is a strong advantage.
• Demonstrated interest in financial markets.

Responsabilités

• Source and evaluate datasets for options and derivatives research.
• Build and maintain robust data pipelines.
• Partner with researchers and traders to understand data needs.

Connaissances

3+ years of experience as a Data Scientist or Data Engineer

Strong Python programming skills

Experience working with financial market data

Excellent communication skills

Outils

Pandas

NumPy

Description du poste

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 role within QRT:

As part of the Data Search & Analytics team, you will support one of QRT's Options trading streams, working closely with quantitative researchers and traders to source, curate and deliver high-quality data that powers systematic options research and trading.

In addition to the core responsibilities outlined above, you will:

• Source, evaluate and onboard datasets relevant to options and derivatives research.
• Partner closely with researchers and traders to understand data requirements and translate them into scalable data solutions.
• Build and maintain robust data pipelines, ensuring the quality, consistency and timeliness of options-related datasets.
• Develop a strong understanding of options market data and contribute to improving QRT's internal data platform and tooling.
• Proactively identify opportunities to enhance data coverage, quality and operational efficiency for the Options business.

Your present skillset:

• 3+ years of experience as a Data Scientist, Data Engineer or in a similar data-focused role; experience supporting quantitative research or trading teams is advantageous.
• Experience working with financial market data; exposure to options, derivatives or volatility data is a strong advantage.
• Strong Python programming skills, with experience using data processing libraries such as Pandas and NumPy.
• Experience building data pipelines and working with large-scale structured and time-series datasets.
• Demonstrated interest in financial markets and the application of data to quantitative research and trading.
• Excellent communication and stakeholder management skills, with the ability to collaborate effectively with researchers, traders, engineers and external data vendors.
• Ability to thrive in a fast-paced, high-performance environment while managing multiple data initiatives simultaneously.

QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.