Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Join a dynamic team to optimise trading models and build cloud-native analytics platforms.
- Company: A leading commodities trading firm focused on innovative data solutions.
- Benefits: Enjoy a competitive salary, bonuses, and comprehensive health and retirement benefits.
- Why this job: Make a real impact by developing tools that enhance trading strategies in a data-driven environment.
- Qualifications: Experienced Python developer with cloud application skills; financial background preferred but not essential.
- Other info: No up-to-date CV required; perfect for those wanting to bridge finance and data science.
The predicted salary is between 72000 - 168000 £ per year.
Job Description
Do you want to work with the data science team and get exposure to various kinds of complex datasets?
At this commodities trading firm, you’ll work directly with trading teams to optimize trading models and build cloud-native platforms for all kinds of analytics.
You don't need any prior financial or commodities trading background.
This platform provides all aspects of the analytics that support the trading desk. You’ll be coming in as they’re completely rebuilding it, transferring from MATLAB to Python. That’s why you’ll partner with both the Data Science and Trading teams to understand the requirements and build them into production.
Your primary role is to build the analytic systems. Of course, as it’s extremely data-driven too, you’ll be encouraged to use analytics and visualisation tools when required, but also given your experience, you’ll be able to put forward new ideas and suggest new tools to use to help improve the platforms.
Specifically, in terms of your experience, you’ll be an experienced Python developer who can bring new ideas to the team. It’s almost essential that you have strong experience of building applications in the cloud (AWS or Azure) with a strong data focus.
Experience in the front office of a financial company, ideally within commodities will also be required, additional technical experience with Snowflake and Terraform would be a huge plus.
You’ll have lots of input into building all kinds of new tools and models and you’ll be able to see the impact of your work. Salary on offer is up to £120,000 plus a bonus which could be as much as 30-40% of your salary. Benefits include comprehensive medical, dental, retirement and life insurance and a range of other policies and programs to make sure you’re taken care of throughout your time in the company.
Want to stay in front office but get closer to data science and commodities? Get in touch.
No up-to-date CV required.
Contact Detail:
Saragossa Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Software Engineer - Get into finance/commodities trading - up to £120,000 Base Salary + 30-40% Bonus
✨Tip Number 1
Familiarise yourself with the specific technologies mentioned in the job description, such as Python, AWS, and Azure. Having hands-on experience or projects showcasing your skills in these areas will make you stand out during discussions.
✨Tip Number 2
Network with professionals in the finance and commodities trading sectors. Attend industry meetups or webinars to connect with people who can provide insights into the role and potentially refer you internally.
✨Tip Number 3
Prepare to discuss how your previous experiences can translate into the trading environment. Think about examples where you've optimised systems or worked with complex datasets, as this will demonstrate your value to the team.
✨Tip Number 4
Show enthusiasm for the transition from MATLAB to Python. Be ready to share your thoughts on best practices in Python development and how you can contribute to building cloud-native platforms effectively.
We think you need these skills to ace Software Engineer - Get into finance/commodities trading - up to £120,000 Base Salary + 30-40% Bonus
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience as a Python developer, especially in building applications in the cloud. Emphasise any relevant projects or roles that showcase your data focus and familiarity with AWS or Azure.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for working with complex datasets and your eagerness to collaborate with both Data Science and Trading teams. Mention how your skills can contribute to optimising trading models and building cloud-native platforms.
Showcase Relevant Experience: If you have experience in the front office of a financial company or with commodities trading, make sure to highlight this in your application. Discuss any specific tools or technologies you've used, such as Snowflake or Terraform.
Demonstrate Problem-Solving Skills: Use your application to illustrate your problem-solving abilities. Provide examples of how you've successfully implemented new ideas or tools in previous roles, particularly in data-driven environments.
How to prepare for a job interview at Saragossa
✨Showcase Your Python Skills
As an experienced Python developer, be prepared to discuss your previous projects and how you've used Python in building applications. Highlight any specific frameworks or libraries you've worked with that are relevant to data analytics.
✨Demonstrate Cloud Experience
Since the role requires strong experience in cloud platforms like AWS or Azure, come ready to talk about your experience in deploying applications in the cloud. Be specific about the tools and services you've used and how they contributed to your projects.
✨Understand the Trading Environment
Even though you don't need a financial background, having a basic understanding of commodities trading will set you apart. Research the firm’s trading strategies and be prepared to discuss how your technical skills can enhance their trading models.
✨Be Ready to Suggest Improvements
The company is looking for someone who can bring new ideas to the table. Think about potential tools or methodologies that could improve their analytics platform and be ready to share these insights during the interview.
