Data Scientist - Macro
Qube Research & Technologies
Qube Research & Technologies is also hiring for this role in Paris.
Tailor my CV for this job, freeView job and applyYour CV rewritten for this role, from your real experience. Sign in with Google, nothing to install.
Got this interview? Our apps help you get the job.
Skills named in this job
Read from the description itself, not inferred.
This role on the market
2,378 open scientist roles across 364 companies are on ApplySarthi right now, most of them in Bengaluru (140), Hyderabad (67), Delhi NCR (34).
- Machine Learning Data Scientist - Consumer ForecastingOpenai
- Data ScientistGartner · delhi ncr
- Senior Robotics/AI Motor Control Scientist, FaunaAmazon
- D2P Data & Analytics Senior Data Scientist - RDT ERPRoche
- Data Scientist [Multiple Positions Available]JPMorgan
What scientist roles keep asking for: Python (63%), Machine learning (48%), SQL (31%), Deep learning (18%), C++ (18%), LLMs (17%), R (17%), Java (16%) — counted across their open postings here.
Data Scientist jobs in the United Kingdom · Data Scientist jobs in London · Remote Data Scientist jobs · NumPy jobs · Python jobs · SQL jobs · pandas jobs
Qube Research & Technologies has 195 open roles listed here.
- Software Engineer – Site Reliability Engineering
- Software Engineer – Site Reliability Engineering
- AWS Cloud Network Engineer
- C++ Developer – ETF Technology & Infrastructure
- Senior Low-Latency C++ Software Engineer
Counted across 14 company job boards, updated as roles open and close.
Preparing for this interview
Interviews for scientist roles keep coming back to Python, Machine learning, SQL, Deep learning. Practise those questions before you sit with Qube Research & Technologies.
Questions you are likely to be asked
- Why do you want to join Qube Research & Technologies?
- What is your experience with Python? Tell me one thing you learned the hard way.
- When would you not use machine learning for a problem?
- Walk me through a model you built, from the data to how it was used.
- How did you know your model was actually good, and not just good on your test set?
Prep Sarthi gives you a free mock interview: an AI interviewer asks you questions like these out loud, from your own CV and this job, and shows your score and your weakest answer.
Practise the Data Scientist - Macro at Qube Research & Technologies interview free →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.
Match this job to your CV
ApplySarthi scores your CV against this role, shows the skills you are missing, and writes a tailored version for the application.
Check my match →Similar open roles
- AI Platform EngineerQube Research & Technologies · mumbai
- Business Analyst – Trading SystemQube Research & Technologies · mumbai
- Data Operations Engineer - PythonQube Research & Technologies · mumbai
- Quantitative ResearcherQube Research & Technologies · mumbai
- Technical Program Manager - IT InfrastructureQube Research & Technologies · mumbai
- 2027 – Graduate or Internship, Infrastructure Engineer Qube Research & Technologies
- 2027 - Internship, Data EngineeringQube Research & Technologies
- 2027 – Internship, Data EngineeringQube Research & Technologies
Need answers during your interview? Try Live Sarthi.
Live Sarthi, an Interview Sarthi app, shows answer suggestions during the call.
- Hidden from supported screen sharingThe overlay stays out of supported Windows screen captures.
- Answers start in about 1.5 secondsResponse time varies with your connection and model.
- From your own CVYour projects and your experience, not a generic script.
- 30 minutes freeThen ₹99 for a 2-day pass with unlimited calls — you pay for the days you are interviewing, not a subscription.
A Windows app, from the same team as ApplySarthi.
Listed on greenhouse · posted 2026-10-16. ApplySarthi collects openings and links to application pages; the role is advertised by Qube Research & Technologies, not by us.