About the Role:
We are currently exploring profiles for a Quant Engineer / Strategist role focused on Data Analytics. This is a position suited for experienced professionals who bring deep understanding of data pipelines, data structures, and practical expertise in Python scripting - especially within a quantitative or financial data context.
This position is ideal for someone with a background in data engineering, analytics, or quant, who is hands-on with tools and technologies.
Key Responsibilities:
- Understand and analyze complex data structures and data pipelines used in financial or investment analytics.
- Leverage Python scripting to automate, clean, transform, or extract insights from large datasets.
- Work closely with quantitative researchers, data teams, and investment professionals to support data needs.
- Help validate and enhance the usability and integrity of analytics-ready datasets.
- Support data sourcing, integration, and validation activities in collaboration with internal stakeholders.
Required Skills & Experience:
- 5-10 years of experience in a Quantitative Engineering / Data Analytics / Data Engineering role.
- Strong Python skills, especially in scripting for data processing.
- Deep understanding of data pipelines, data modeling, and data structures in complex environments.
- Familiarity with large datasets and experience working in financial or investment domains is preferred.
- Ability to work independently, exploring solutions and collaborating across cross-functional teams.
Nice to Have:
- Exposure to quantitative research workflows, financial markets, or asset management environments.
- Familiarity with tools like Pandas, NumPy, SQL, or data validation frameworks.
- Prior experience working in a buy-side, investment bank, or financial analytics team.
Argyll Scott Consulting Pte Ltd
