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- Tasks: Join our team to enhance a large Python codebase for data-driven research.
- Company: Be part of a dynamic Portfolio Engineering team focused on innovation.
- Benefits: Enjoy flexible working options and opportunities for professional growth.
- Why this job: Work on impactful projects that improve system performance and scalability.
- Qualifications: 4+ years in Python engineering with strong skills in data libraries.
- Other info: Ideal for those passionate about solving complex problems in tech.
The predicted salary is between 36000 - 60000 £ 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 employer: Block MB
Contact Detail:
Block MB Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Python Engineer - Research
✨Tip Number 1
Familiarise yourself with the specific libraries mentioned in the job description, such as NumPy, xarray, and pandas. Being able to discuss your experience with these tools in detail will show that you’re not just a generalist but someone who can hit the ground running.
✨Tip Number 2
Prepare examples of how you've optimised Python code in the past. Be ready to share specific metrics or improvements you've achieved, as this will demonstrate your ability to enhance system performance effectively.
✨Tip Number 3
Engage with the Python community online, especially in forums related to data science and engineering. This can help you stay updated on best practices and trends, which you can reference during discussions with our team.
✨Tip Number 4
If you have experience in quantitative finance or scientific computing, be sure to highlight this in conversations. It’s a nice-to-have for this role, and showcasing relevant projects can set you apart from other candidates.
We think you need these skills to ace Python Engineer - Research
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 previous projects, especially those that involved performance improvements or complex multi-module systems.
Craft a Strong Cover Letter: In your cover letter, express your passion for Python and problem-solving. Mention specific examples of how you've used data-driven insights in your past roles to make engineering decisions. This is your chance to showcase your analytical skills and enthusiasm for the role.
Showcase Relevant Projects: If you have worked on notable projects, especially in quantitative finance or scientific computing, include them in your application. Describe your role, the technologies used, and the impact of your work, particularly any performance optimisations you achieved.
Proofread and Edit: Before submitting your application, take the time to proofread your documents. Check for any grammatical errors or typos, and ensure that your writing is clear and concise. A well-presented application reflects your attention to detail and professionalism.
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, especially 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 Python and data structures, as well as scenarios where you had to optimise code for performance.
