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For Companies At a Glance
- Tasks: Join our team to enhance a large Python codebase for data-driven research.
- Company: We're a leading firm in portfolio engineering, focused on innovation and performance.
- Benefits: Enjoy flexible working options and a collaborative environment with great perks.
- Why this job: Be part of a dynamic team solving complex problems and making impactful decisions.
- Qualifications: 4+ years in Python engineering, with strong skills in NumPy, xarray, or pandas.
- Other info: Ideal for those passionate about quantitative finance and large-scale data systems.
The predicted salary is between 43200 - 72000 £ per year.
About the Role:
My client are seeking a Python Research Engineer with 4+ years of experience to join their Portfolio Engineering team. In this role, you will work on a large, production-grade Python codebase to help drive the design, performance, and scalability of data-driven research and engineering systems. The ideal candidate is analytical, performance-oriented, and passionate about leveraging Python to solve complex problems.
Responsibilities:
- Contribute to the development and maintenance of a large, modular Python codebase
- Collaborate with researchers and engineers to build robust, scalable systems for portfolio analysis and optimization
- Work with data structures and libraries such as NumPy, xarray, or pandas to process and analyze large datasets
- Identify performance bottlenecks and implement optimizations, improving system speed and efficiency
- Use data-driven insights to guide engineering decisions and system design
- Maintain clean, well-documented, and testable code
Requirements:
- 1–5 years of experience in a Python engineering or research engineering role
- Proven experience working on complex, multi-module Python projects
- Strong proficiency in at least one of: NumPy, xarray, or pandas
- Demonstrated ability to improve system performance
- Experience using data to make informed technical or product decisions
- Excellent problem-solving and communication skills
Nice to Have:
- Experience in quantitative finance, scientific computing, or large-scale data systems
- Familiarity with CI/CD workflows and version control (Git)
- Experience working in a research or cross-functional team environment
Python Engineer - Research (London Area) employer: Block MB
Contact Detail:
Block MB Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Python Engineer - Research (London Area)
✨Tip Number 1
Familiarise yourself with the specific libraries mentioned in the job description, like NumPy, xarray, and pandas. Being able to discuss your experience with these tools in detail will show that you're not just a Python expert but also someone who can hit the ground running.
✨Tip Number 2
Prepare to discuss any past projects where you've optimised performance in Python. Be ready to share specific examples of how you identified bottlenecks and what impact your changes had on system efficiency.
✨Tip Number 3
Highlight your collaborative skills by preparing examples of how you've worked with cross-functional teams in the past. This role requires collaboration with researchers and engineers, so demonstrating your ability to communicate effectively is key.
✨Tip Number 4
Stay updated on trends in quantitative finance and scientific computing. Showing that you have a genuine interest in these areas can set you apart from other candidates and demonstrate your passion for the role.
We think you need these skills to ace Python Engineer - Research (London Area)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python and any relevant libraries like NumPy, xarray, or pandas. Emphasise your contributions to complex projects and any performance improvements you've achieved.
Craft a Strong Cover Letter: In your cover letter, express your passion for Python and data-driven research. Mention specific examples of how you've solved complex problems in previous roles and how you can contribute to the Portfolio Engineering team.
Showcase Relevant Projects: If you have worked on notable projects, especially those involving large datasets or performance optimisation, include them in your application. Briefly describe your role and the impact of your work.
Highlight Collaboration Skills: Since the role involves working with researchers and engineers, emphasise your teamwork and communication skills. Provide examples of successful collaborations that led to improved outcomes in your previous positions.
How to prepare for a job interview at Block MB
✨Showcase Your Python Expertise
Be prepared to discuss your experience with Python in detail. Highlight specific projects where you've worked on complex, multi-module codebases and be ready to explain the challenges you faced and how you overcame them.
✨Demonstrate Your Analytical Skills
Since the role requires a strong analytical mindset, come equipped with examples of how you've used data to drive decisions. Discuss any performance optimisations you've implemented and the impact they had on system efficiency.
✨Familiarise Yourself with Relevant Libraries
Make sure you have a solid understanding of libraries like NumPy, xarray, or pandas. Be ready to discuss how you've used these tools in past projects, particularly in relation to processing and analysing large datasets.
✨Prepare for Technical Questions
Expect technical questions that assess your problem-solving abilities. Practice coding problems related to performance bottlenecks and system design, as well as discussing CI/CD workflows and version control if applicable.
