Back to jobs

Data Scientist - Macro

Reads like a Data Governance role: data quality and governance.

Paris

Pay
Pay not listed
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting

What you’ll work on

Full posting
  • Identify datasets that meet research and trading needs with Quants, PMs and Traders

  • Evaluate and onboard new Macro datasets, including Rates, bonds, swaps and alternative data

  • Engage external data providers and assess their APIs and data delivery

  • Build Python tools and pipelines to extract, clean and analyse financial data

  • Investigate discrepancies across providers in identifiers, pricing and timestamps

From the employer’s posting
Collaborate with Quantitative Researchers, Portfolio Managers and Traders to understand their data requirements and identify suitable datasets for research and trading strategies
Manage the discovery, evaluation and onboarding of new datasets, with a focus on Macro markets, including Rates, bonds, swaps, derivatives and alternative data
Engage directly with external data providers to understand their offerings, assess APIs and investigate data availability, structure and delivery mechanisms
Develop Python tools and data pipelines to extract, clean, normalise and analyse financial datasets from multiple sources
Investigate discrepancies across data providers, including differences in instrument identifiers, pricing conventions, timestamps and reference data

Tools in this posting

  • Python
  • SQL
  • NumPy
  • pandas
Source — Tool mentions in context
- Develop Python tools and data pipelines to extract, clean, normalise and analyse financial datasets from multiple sources -
- Strong Python programming skills, including experience with data analysis libraries such as Pandas and NumPy -
- Good SQL skills and experience working with structured financial datasets -

Posting record

Report an error
Status in our records
Live
First seen by us
Oct 18, 2026 · 14 days ago
Recorded sightings
24
Last seen by us
Nov 1, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

Your next step

  • Have your resume and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.
  • Ask the employer about the pay range before committing time to the process.

Complete your application on job-boards.greenhouse.io. The employer’s form will show what is required.

Already applied? Track this application

Job description

View original posting ↗

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.

You will work at the intersection of financial markets, data science and engineering, supporting the discovery, evaluation and integration of financial datasets used across quantitative research and trading. The role combines technical expertise with an understanding of Macro markets, working closely with Quantitative Researchers, Portfolio Managers and Traders to translate business requirements into practical data solutions. You will engage directly with external data providers, assess existing data assets and identify opportunities to expand the firm's data capabilities.

Your future role within QRT

  • Collaborate with Quantitative Researchers, Portfolio Managers and Traders to understand their data requirements and identify suitable datasets for research and trading strategies

  • Evaluate existing data assets and external vendor offerings, assessing coverage, quality, consistency and suitability for specific financial applications

  • Manage the discovery, evaluation and onboarding of new datasets, with a focus on Macro markets, including Rates, bonds, swaps, derivatives and alternative data

  • Engage directly with external data providers to understand their offerings, assess APIs and investigate data availability, structure and delivery mechanisms

  • Develop Python tools and data pipelines to extract, clean, normalise and analyse financial datasets from multiple sources

  • Investigate discrepancies across data providers, including differences in instrument identifiers, pricing conventions, timestamps and reference data

  • Maintain and improve the quality and consistency of existing datasets, proactively resolving issues and identifying opportunities to enhance data coverage

  • Collaborate with engineering teams to automate data ingestion, validation and integration processes, ensuring reliable delivery into research and trading environments

Your present skillset

  • Minimum 2 years of relevant professional experience in Data Science, Data Analysis, Data Engineering or a similar role within financial markets

  • Practical understanding of financial markets and instruments, with exposure to Macro, Fixed Income, Rates, Credit or related asset classes

  • Strong Python programming skills, including experience with data analysis libraries such as Pandas and NumPy

  • Good SQL skills and experience working with structured financial datasets

  • Experience sourcing, analysing and processing financial data, with an understanding of data quality, validation and consistency across multiple sources

  • Ability to understand financial concepts and communicate effectively with Quantitative Researchers, Portfolio Managers, Traders and external data vendors

  • Strong analytical and problem solving skills, with the ability to investigate unfamiliar datasets and identify appropriate solutions independently

  • Familiarity with external data providers, financial data platforms and API integration

  • Ability to manage competing priorities, take ownership of data initiatives and collaborate effectively across technical and business functions

  • Degree in a quantitative discipline such as Mathematics, Statistics, Computer Science, Physics, Engineering or Finance; a postgraduate qualification is beneficial

  • Experience developing data pipelines, automating data workflows or supporting production data infrastructure is beneficial

  • Knowledge of financial data concepts such as yield curves, instrument reference data, market data and pricing conventions is advantageous

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.

 

Source details

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay

No pay amount identified in the saved description.

Location & working pattern

Paris

Working pattern and location restrictions need checking in the full posting.

Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

See how this role fits your experience

Add your resume to compare the role’s scope, tools and requirements with your experience.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.