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 employer: Quant Blueprint LLC
As a leading employer in the finance sector, we offer Quantitative Developers the opportunity to work in dynamic locations like London or Dubai, where innovation meets a vibrant work culture. Our commitment to employee growth is evident through continuous learning opportunities and collaboration with experienced professionals, fostering an environment that encourages curiosity and entrepreneurial thinking. Join us to be part of a team that values rigorous analysis and creativity in developing cutting-edge trading strategies.
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative Developer, Systematic Equities
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even just grab a coffee with someone who works in systematic equities. Building relationships can open doors that a CV just can't.
✨Show Off Your Skills
When you get the chance to chat with potential employers, don’t hold back on showcasing your technical skills. Bring up your experience with Python, machine learning, and data manipulation. Let them know you’re ready to dive into those large financial datasets!
✨Ask Smart Questions
During interviews, ask insightful questions about their trading strategies and data sources. This shows you’re not just interested in the role but also genuinely curious about how they operate. Plus, it gives you a chance to demonstrate your knowledge of quantitative finance.
✨Apply Through Our Website
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
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the job description. Highlight your proficiency in Python, machine learning, and any relevant experience with systematic trading strategies.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about quantitative finance and how your background makes you a great fit for the role. Be sure to mention specific projects or experiences that showcase your analytical skills.
Showcase Your Technical Skills:Don’t shy away from detailing your experience with data science tools like Jupyter, pandas, and numpy. We want to see how you've applied these in real-world scenarios, especially in relation to large financial datasets.
Apply Through Our Website:For the best chance of getting noticed, make sure to apply directly through our website. It helps us keep track of applications and ensures you’re considered for the role!
How to prepare for a job interview at Quant Blueprint LLC
✨Know Your Tech Stack
Make sure you’re well-versed in the modern data science tools mentioned in the job description, like Jupyter, pandas, and sklearn. Brush up on your Python skills and be ready to discuss how you've used these tools in past projects.
✨Showcase Your Analytical Skills
Prepare to demonstrate your problem-solving abilities by discussing specific examples where you've tackled complex data challenges. Be ready to explain your thought process and the statistical techniques you employed to derive insights.
✨Understand Systematic Trading
Familiarise yourself with systematic trading strategies and be prepared to discuss your experience in this area. Highlight any relevant projects or roles where you’ve developed or implemented trading strategies, especially in equities.
✨Communicate Effectively
Since excellent communication is key, practice explaining complex concepts in simple terms. Be ready to discuss how you’ve collaborated with cross-functional teams and how you adapt to fast-paced environments.
