At a Glance
- Tasks: Develop systematic trading strategies and analyse large financial datasets.
- Company: Leading finance firm with a focus on innovation and collaboration.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Fast-paced environment with excellent career advancement potential.
- Why this job: Join a dynamic team and make an impact in the world of finance.
- Qualifications: Degree in STEM, strong Python skills, and experience in quantitative finance.
The predicted salary is between 60000 - 80000 £ per year.
Location: London or Dubai preferred.
Principal Responsibilities
- Work alongside the Senior Portfolio Manager on developing systematic trading strategies, with a primary focus on:
- Idea generation
- Data gathering and analysis
- Model implementation and back testing for systematic global equities strategies
- Explore, analyze, and harness large financial datasets using various statistical learning techniques.
- Work with multiple vendor data sets: assessing, cleaning, creating features.
- Implement flexible, scalable and efficient machine learning framework using existing features.
- Optimize code for larger scale work.
- Create new features using additional database (KDB preferred).
Preferred Technical Skills
- Proficient in modern data science tools stacks (Jupyter, pandas, numpy, sklearn) with machine learning experience.
- Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or related STEM field from top ranked University.
- Expert in Python (KDB/Q is a plus).
- Demonstrated knowledge of quantitative finance, mathematical modelling, statistical analysis, regression, and probability theory.
- Excellent communication, problem‑solving, and analytical skills, with the ability to quickly understand and apply complex concepts.
Preferred Experience
- 3+ years of experience working in a systematic trading environment with a focus on equities.
- 3+ years of experience working with multiple vendor data sets and, in particular, manipulating data (assessing, cleaning, creating features, etc.).
- Demonstrated theoretical understanding of Machine Learning with 2-3+ years of hands‑on experience in the applications.
- Experience collaborating effectively with cross functional teams, multitasking and adapting in a fast‑paced environment.
Highly Valued Relevant Attributes
- Strong intuition about feature/data prediction power.
- Extremely rigorous, critical thinker, self‑motivated, detail‑oriented, and able to work independently in a fast‑paced environment.
- Entrepreneurial mindset.
- Curiosity and eagerness to learn and grow professionally.
Quantitative Developer, Systematic Equities in London employer: Quant Blueprint LLC
As a Quantitative Developer in Systematic Equities, you will thrive in a dynamic and innovative environment that values collaboration and professional growth. Our London or Dubai offices offer a vibrant work culture, competitive benefits, and the opportunity to work with cutting-edge data science tools while developing impactful trading strategies. Join us to enhance your skills and contribute to a forward-thinking team dedicated to excellence in quantitative finance.
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative Developer, Systematic Equities in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with alumni from your university. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving data analysis and machine learning. This is your chance to demonstrate your expertise in Python and other tools, so make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice coding challenges and be ready to discuss your past experiences with systematic trading and data manipulation.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Quantitative Developer, Systematic Equities in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in systematic trading and data analysis. We want to see how your skills align with the role, so don’t be shy about showcasing your relevant projects and achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about quantitative finance and how your background makes you a perfect fit for our team. Keep it concise but impactful!
Showcase Your Technical Skills:Since we’re looking for someone proficient in Python and data science tools, make sure to mention specific projects where you’ve used these skills. We love seeing real-world applications of your knowledge!
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 don’t miss out on any important updates from our team!
How to prepare for a job interview at Quant Blueprint LLC
✨Know Your Data Science Tools
Make sure you're well-versed in the modern data science tool stack mentioned in the job description, like Jupyter, pandas, and sklearn. Brush up on your Python skills, as you'll likely be asked to demonstrate your proficiency during the interview.
✨Showcase Your Analytical Skills
Prepare to discuss your experience with data gathering, analysis, and model implementation. Have specific examples ready that highlight your problem-solving abilities and how you've tackled complex datasets in previous roles.
✨Understand Systematic Trading
Familiarise yourself with systematic trading strategies and the role of quantitative finance. Be ready to explain how you've contributed to developing or optimising trading strategies in your past positions, especially in equities.
✨Demonstrate Your Curiosity
Exhibit your eagerness to learn and grow by asking insightful questions about the company's approach to machine learning and data analysis. This shows that you're not just looking for a job, but are genuinely interested in contributing to their success.
