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Qube Research & Technologies

Data Scientist - Options

LocationParis
Typefull-time
SeniorityMid
Experience3+ yrs
DepartmentMF-DSA
Company size501–1,000 people
PostedJun 29, 2026 · 3mo ago
Verified live3h ago
At a glanceSummarised by Seekless from the posting.
Must have8
3+ years of experience as a Data Scientist, Data Engineer or in a similar data-focused role
Strong Python programming skills
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
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
Nice to have3
Experience supporting quantitative research or trading teams
Experience working with financial market data
Exposure to options, derivatives or volatility data
Eligibility4
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
Offer initiatives and programs to enable employees achieve a healthy work-life balance
Skills
Python
Pandas
NumPy
About the company
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.
Responsibilities
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.
Legal
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.
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