Data Scientist

Coolabah Capital Investments; Greater London; On-site; GBP 70,000 - 110,000; Full time

Benefits offered by this job

Equity participation

Bonus pool

Job summary

Coolabah Capital Investments in London is seeking a data scientist to apply quantitative methods to fixed income markets, focusing on asset pricing, portfolio management modelling, and research-driven engineering tasks.

You will work with R tidyverse, Python and SQL, munging large datasets, back-testing models, and delivering clear written methods and visualisations within pre‑agreed timetables. Equity participation may be available.

Qualifications

• Ideally a reliable quant researcher or data scientist with an advanced degree and industry experience.
• Experience applying data science techniques to real-world problems.
• Willingness to make a long-term commitment to the role.

Responsibilities

• Apply data science skills to fixed income markets and asset pricing models.
• Lead long‑term research and production‑grade engineering tasks.
• Munge large datasets from multiple sources and benchmark methods.
• Back‑test models, produce visuals, and write clear methodology papers.
• Deliver outputs on pre‑agreed timetables and drive innovation.

Skills

Team player

Statistical modelling

Data munging & analysis

Engineering best practices

High-intensity work ethic

Knowledge of financial markets not req

Education

Advanced degree in statistics/engineering/science/actuarial

Tools

R tidyverse

Python Pandas

SQL

data.table

Job description

• Rapidly growing fixed income fund manager
• Research and coding intensive data science role
• Competitive compensation including performance-based bonus

Role/Responsibilities

We are a successful fixed‑income fund manager running multiple portfolios/strategies looking for a full‑time data scientist who is able to apply a range of data science skills to the fixed income market.

Reporting to the lead data scientist as well as portfolio managers, the role is full‑time and will span long‑term project research and engineering duties. In particular the role will involve: using R and other languages for asset pricing and portfolio management modelling; managing and munging large datasets from multiple sources; benchmarking research methods against state‑of‑the‑art academic literature; back‑testing models against suitable benchmarks and metrics; driving model development and research into production grade systems; producing intuitive and immersive data visualisations; producing written method papers that are clear and well‑communicated; delivering outputs/results according to pre‑agreed timetables; and generally investigating ways in which our technical methods can be enhanced.

Pay will be market competitive in all respects with the opportunity to earn significant bonuses based on performance and equity participation in the business.

Skills/Experience

Ideally suits a reliable quant researcher or data scientist with an advanced degree in stats/engineering/science/actuarial who has applied data science techniques in industry, and wants to make a long‑term commitment to their next position. Suitable candidates will possess the following attributes:

• Team player
• Excellent statistical modelling skills
• Excellent data munging and analysis skills.
• Understanding of good engineering practices when contributing to large shared code bases
• High‑intensity work ethic + willingness to work outside normal hours
• No prerequisite financial markets knowledge/experience required.

This role uses the R tidyverse framework for data munging. If unfamiliar with tidyverse, then experience with R data.table, Python Pandas, SQL or similar is required together with the willingness to transition to R tidyverse.

• It is expected a market‑competitive contract will be agreed with the opportunity to participate in the bonus pool and equity ownership scheme. The work will be demanding but also highly creative with the right candidate able to assume significant responsibilities and drive innovation.