Data Scientist - Macro

Description

The company is a global quantitative and systematic investment manager trading across all liquid asset classes worldwide. It is a technology and data driven group that takes a scientific approach to investing, and it combines data, research, technology and trading expertise to tackle hard problems.

The role sits between financial markets, data science and engineering. You will help find, assess and bring in financial datasets used by quantitative research and trading, with a focus on Macro markets. You will work closely with Quantitative Researchers, Portfolio Managers and Traders to turn their business needs into practical data solutions, speak directly with external data providers, review existing data assets and look for ways to widen the firm's data capabilities.

Responsibilities

• Work with Quantitative Researchers, Portfolio Managers and Traders to learn what data they need and pick suitable datasets for research and trading strategies.
• Review internal data assets and outside vendor offerings, judging coverage, quality, consistency and fit for particular financial uses.
• Lead the discovery, evaluation and onboarding of new datasets, focusing on Macro markets including Rates, bonds, swaps, derivatives and alternative data.
• Talk directly with external data providers about their products, review their APIs and check data availability, structure and delivery methods.
• Build Python tools and data pipelines that extract, clean, normalise and analyse financial data from several sources.
• Track down differences between data providers in instrument identifiers, pricing conventions, timestamps and reference data.
• Keep existing datasets accurate and consistent, fix problems before they spread, and spot ways to extend coverage.
• Partner with engineering teams to automate ingestion, validation and integration so data reaches research and trading environments reliably.

Requirements

• At least 2 years of relevant professional experience in Data Science, Data Analysis, Data Engineering or a similar role within financial markets.
• Working knowledge of financial markets and instruments, with exposure to Macro, Fixed Income, Rates, Credit or related asset classes.
• Strong Python skills, including hands-on use of data analysis libraries such as Pandas and NumPy.
• Good SQL skills and experience with structured financial data.
• Experience sourcing, analysing and processing financial data, with a clear grasp of data quality, validation and consistency across sources.
• Ability to understand financial concepts and explain them clearly to Quantitative Researchers, Portfolio Managers, Traders and external data vendors.
• Strong analytical and problem solving skills, and the ability to investigate unfamiliar datasets and find solutions on your own.
• Familiarity with external data providers, financial data platforms and API integration.
• Ability to juggle competing priorities, own data initiatives and work well across technical and business teams.
• A degree in a quantitative field such as Mathematics, Statistics, Computer Science, Physics, Engineering or Finance.

Conditions

Equal opportunity employer that values diversity.

Benefits

• A postgraduate qualification is beneficial.
• Experience building 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.
• Initiatives and programmes that support a healthy work-life balance.