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.
Senior Quantitative Researcher, Systematic Equities employer: Quant Blueprint LLC
As a Senior Quantitative Researcher in Systematic Equities, you will thrive in a dynamic and innovative environment that champions professional growth and collaboration. Our London or Dubai offices offer a vibrant work culture, competitive benefits, and the opportunity to work with cutting-edge data science tools while contributing to impactful trading strategies. Join us to be part of a forward-thinking team that values curiosity, critical thinking, and an entrepreneurial spirit.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Quantitative Researcher, Systematic Equities
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or conferences related to quantitative finance. You never know who might have a lead on your dream job or can offer valuable insights.
✨Show Off Your Skills
Create a portfolio showcasing your projects and analyses. Use GitHub to share your code and demonstrate your proficiency in Python and data science tools. This will give potential employers a taste of what you can bring to the table.
✨Ace the Interview
Prepare for technical interviews by brushing up on your machine learning concepts and quantitative finance knowledge. Practice coding challenges and be ready to discuss your past experiences in detail. Confidence is key!
✨Apply Through Us
Don’t forget to check out our website for openings! Applying directly through us not only shows your interest but also gives you a better chance of landing that Senior Quantitative Researcher role. We’re rooting for you!
We think you need these skills to ace Senior Quantitative Researcher, Systematic Equities
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Senior Quantitative Researcher role. Highlight your expertise in Python, machine learning, and any relevant projects you've worked on that showcase your analytical skills.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about systematic trading strategies and how your background makes you a perfect fit for our team. Don't forget to mention your experience with large financial datasets!
Showcase Your Problem-Solving Skills:In your application, give examples of how you've tackled complex problems in previous roles. We love seeing candidates who can think critically and apply their knowledge to real-world challenges, especially in a fast-paced environment.
Apply Through Our Website:We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at StudySmarter!
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. Brush up on Jupyter, pandas, numpy, and sklearn, and be ready to discuss how you've used these tools in your previous roles.
✨Showcase Your Quantitative Skills
Prepare to demonstrate your understanding of quantitative finance and statistical analysis. Be ready to explain complex concepts like regression and probability theory in a way that shows you can apply them practically in a trading environment.
✨Highlight Your Experience with Vendor Data Sets
Since working with multiple vendor data sets is crucial for this role, come prepared with specific examples of how you've assessed, cleaned, and created features from such data. This will show your hands-on experience and problem-solving skills.
✨Emphasise Your Collaborative Spirit
This position requires effective collaboration with cross-functional teams. Share examples of past experiences where you successfully worked with others, adapted to fast-paced environments, and contributed to team goals. It’s all about showing you can thrive in a dynamic setting!
