Quantitative Developer
Team: Company
Location: London UK
Workplace Type: onsite
Responsibilities
- Collaborate closely with product managers, research analysts and other engineers to define project scope, translate research into product requirements, and deliver concrete technical solutions.
- Maintain, extend and improve Intropic’s suite of financial-data products, from backend data services to client-facing features.
- Design, implement and ship clean, well-tested, production-ready Python code and reusable Python libraries used across the stack.
- Build and maintain data processing pipelines that ingest, transform and validate large and heterogeneous financial datasets.
- Build production REST APIs and data services, and use SQL to analyse large relational datasets.
- Deploy production-quality code to cloud infrastructure (cloud providers, CI/CD pipelines) and own the end-to-end release process.
- Work with analysts to operationalise quantitative research: production-wise models, automate experiments, and ensure reproducible results.
Qualifications - Required
- STEM graduate (or final-year student) with demonstrable coding ability.
- Strong Python skills (other OOP languages such as Java or C++ are welcome and seen as a plus).
- Practical experience with SQL and relational databases
- Comfortable with the command line and modern version-control workflows (example: GitHub / GitLab / Bitbucket).
- Strong communicator, able to explain technical work to both technical and non-technical audiences.
- Independent, self-driven learner who takes ownership and can work across disciplines.
- Familiarity with automated testing and general software engineering best practices (code review, CI concepts).
Qualifications - Preferable
- 0–2 years professional experience in a software engineering, quantitative developer, or data engineering role. Experience within the finance industry is a strong plus.
- Good working knowledge of NumPy and Pandas.
- Familiarity with backend development and async programming in Python / modern Python frameworks.
- Experience with containerisation and cloud deployments (Docker, cloud platforms such as AWS).
- Practical exposure to financial data via university projects, internships or full-time work.
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