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- Tasks: Design and develop robust data systems for trading and research.
- Company: Leading trading firm in London with a focus on innovation.
- Benefits: Competitive compensation, private healthcare, and catered meals.
- Other info: Join a dynamic team with exciting growth opportunities.
- Why this job: Make a real impact in financial markets using your Python skills.
- Qualifications: Proficiency in Python, SQL, and data engineering required.
The predicted salary is between 60000 - 80000 £ per year.
A leading trading firm in London is seeking a Python Developer for their Data & Analytics Team. In this role, you will design and develop robust data systems supporting trading and research. Your expertise in Python, SQL, and data engineering will drive meaningful results in real-time financial markets.
Competitive compensation and excellent perks await the ideal candidate, including private healthcare and catered meals.
Python Developer: Data & Analytics for Options Market Making employer: Maven
Contact Detail:
Maven Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Python Developer: Data & Analytics for Options Market Making
✨Tip Number 1
Network like a pro! Reach out to folks in the trading and data analytics space on LinkedIn. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a GitHub repository showcasing your Python projects, especially those related to data systems or analytics. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for technical interviews by brushing up on SQL and data engineering concepts. Practice coding challenges that focus on real-time data processing to impress your interviewers.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Python Developer: Data & Analytics for Options Market Making
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your Python and SQL skills, as well as any relevant experience in data engineering. We want to see how your background aligns with the role, so don’t be shy about showcasing your achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about data systems and how you can contribute to our Data & Analytics Team. Keep it concise but impactful – we love a good story!
Showcase Relevant Projects: If you've worked on projects that involve trading, data analysis, or real-time systems, make sure to mention them. We’re keen to see how your hands-on experience can bring value to our team.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. Plus, it’s super easy!
How to prepare for a job interview at Maven
✨Know Your Python Inside Out
Make sure you brush up on your Python skills before the interview. Be prepared to discuss your previous projects and how you've used Python to solve complex problems, especially in data systems. Practising coding challenges can also help you demonstrate your technical prowess.
✨SQL Savvy is Key
Since SQL is crucial for this role, ensure you're comfortable with writing queries and optimising database performance. You might be asked to solve a problem on the spot, so review common SQL functions and be ready to explain your thought process as you work through them.
✨Understand the Trading Landscape
Familiarise yourself with the basics of trading and market making. Knowing how data analytics impacts trading decisions will show your genuine interest in the role and the company. It’s a great way to connect your technical skills with the business side of things.
✨Prepare Questions that Matter
Interviews are a two-way street, so think of insightful questions to ask about the team, projects, and company culture. This not only shows your enthusiasm but also helps you gauge if the firm is the right fit for you. Ask about their tech stack or how they approach data challenges in real-time markets.