At a Glance
- Tasks: Join a team to optimise trading strategies using algorithmic trading and predictive models.
- Company: Harrington Starr, a leader in the financial technology sector.
- Benefits: Competitive salary, collaborative environment, and opportunities for impactful work.
- Other info: Dynamic role with significant career growth potential in a fast-paced industry.
- Why this job: Make a real difference in live markets with cutting-edge technology and data science.
- Qualifications: Strong background in statistics or data science, plus advanced Python and R skills.
The predicted salary is between 60000 - 80000 € per year.
Harrington Starr is seeking a Quantitative Analyst to join its Execution Research team in Greater London. This role focuses on algorithmic trading and market making, leveraging predictive models for real-time sports betting markets.
Candidates should have a strong background in statistics or data science, along with advanced skills in Python and R. This role offers high impact within a collaborative environment, spanning from research through to production deployment, optimizing trading strategies.
Market-Making Quant Analyst: Execution & Live Markets in London employer: Harrington Starr
Harrington Starr is an exceptional employer, offering a dynamic and collaborative work culture that fosters innovation and growth. As a Market-Making Quant Analyst in Greater London, you will have the opportunity to make a significant impact on algorithmic trading strategies while working alongside talented professionals in the field. The company prioritises employee development, providing access to cutting-edge resources and training, ensuring that you can thrive in your career and contribute meaningfully to the team's success.
StudySmarter Expert Advice🤫
We think this is how you could land Market-Making Quant Analyst: Execution & Live Markets in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can land you that dream role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects in Python and R. We want to see your predictive models in action, especially if they relate to algorithmic trading or market making.
✨Tip Number 3
Prepare for those interviews! Brush up on your statistics and data science knowledge. We recommend practicing common quant interview questions and even doing mock interviews with friends or mentors.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Market-Making Quant Analyst: Execution & Live Markets in London
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your background in statistics or data science. We want to see how your skills in Python and R can contribute to our algorithmic trading and market-making efforts.
Tailor Your Application:Don’t just send a generic CV! Customise your application to reflect the specific requirements of the Market-Making Quant Analyst role. We love seeing candidates who take the time to align their experience with what we’re looking for.
Be Clear and Concise:When writing your application, keep it straightforward. We appreciate clarity, so make sure your points are easy to understand and directly related to the role. Avoid jargon unless it’s relevant!
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of applications better and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Harrington Starr
✨Know Your Algorithms
Make sure you brush up on your knowledge of algorithmic trading and market-making strategies. Be prepared to discuss specific models you've worked with and how they can be applied to real-time sports betting markets.
✨Show Off Your Coding Skills
Since advanced skills in Python and R are crucial for this role, practice coding challenges beforehand. You might be asked to solve a problem on the spot, so being comfortable with both languages will give you an edge.
✨Statistics is Key
Given the emphasis on statistics and data science, be ready to explain statistical concepts and how you've used them in past projects. Bring examples that showcase your analytical thinking and problem-solving abilities.
✨Collaborative Mindset
This role thrives in a collaborative environment, so be prepared to discuss how you've worked in teams before. Highlight experiences where you contributed to research or production deployment, showing that you can optimise trading strategies together with others.
