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- Tasks: Research, test, and deploy innovative trading strategies using Python.
- Company: Dynamic financial tech firm focused on quantitative research.
- Benefits: Catered meals, generous home office budget, health benefits, and competitive salary.
- Why this job: Join a team that values creativity and offers real impact in financial markets.
- Qualifications: Bachelor’s in relevant field with strong coding and problem-solving skills.
- Other info: Exciting opportunities for growth in a fast-paced environment.
The predicted salary is between 120000 - 200000 £ per year.
We are looking for a research engineer to research, test, and deploy new trading strategies, as well as to design and build research infrastructure to test trading ideas. Candidates focusing on strategy development should be strong quantitative problem solvers interested in identifying and monetizing statistical patterns in the financial markets and also adept at implementing their ideas in Python. We are looking for someone who is both intellectually curious and self-sufficient to help maintain and develop various trading strategies. Candidates with software implementation skills and comfort in implementing both performant code and designing user-friendly tools will also be strongly considered. We are looking for someone who is effective at building usable software quickly and correctly to extend the scope of our quantitative research and coverage of our trading strategies.
Duties
- Writing Python code to express statistical ideas and relationships between securities
- Coming up with and iterating upon novel ideas and hypotheses about market participants and dynamics
- Collaborating with teammates on new trading ideas
- Extending existing research tools to support novel use cases and needs, as well as designing and implementing new tools to support research and trading needs
Qualifications
- Bachelor’s in computer science, mathematics, physics, or similar field, with strong familiarity with statistics and quantitative problem-solving
- Self-sufficient ability to implement statistical ideas in code
- Strong familiarity with Python and C++ (or equivalent) preferred
- Interest in financial markets or learning more about financial markets
- Previous experience in quantitative finance or trading is a plus, but is not required
Benefits
- Catered meals and bountiful snacks
- Generous budget for home office equipment
- Health / pension
- Fitness and wellness benefits
- Base compensation: £150,000-250,000 with additional discretionary annual performance bonus
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Research Engineer employer: Ansatz Capital
Contact Detail:
Ansatz Capital Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python projects, especially those related to trading strategies or quantitative analysis. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your problem-solving skills. Be ready to tackle technical questions and coding challenges that test your quantitative abilities. Practising with mock interviews can really help you feel more confident.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Research Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python and any quantitative problem-solving skills. We want to see how your background aligns with the role, so don’t be shy about showcasing relevant projects or coursework!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to express your intellectual curiosity and passion for financial markets. Let us know why you’re excited about the opportunity to develop trading strategies and how you can contribute to our team.
Showcase Your Projects: If you've worked on any relevant projects, especially those involving statistical analysis or trading strategies, make sure to mention them. We love seeing practical applications of your skills, so include links to your GitHub or any other portfolio if possible!
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 the role. Plus, it shows us you’re keen on joining the StudySmarter team!
How to prepare for a job interview at Ansatz Capital
✨Know Your Python Inside Out
Since the role heavily involves writing Python code, make sure you brush up on your skills. Be prepared to discuss your previous projects and how you've implemented statistical ideas in Python. Practising coding challenges can also help you demonstrate your problem-solving abilities.
✨Show Your Curiosity
The company is looking for someone who is intellectually curious about financial markets. Prepare some thoughtful questions about their trading strategies or recent market trends. This shows that you're not just interested in the job, but also in the industry as a whole.
✨Prepare for Collaboration
Collaboration is key in this role, so think of examples where you've worked effectively in a team. Be ready to discuss how you’ve contributed to group projects, especially those involving strategy development or research tools. Highlight your ability to communicate complex ideas clearly.
✨Demonstrate Your Problem-Solving Skills
As a research engineer, you'll need to identify and monetise statistical patterns. Prepare to discuss specific problems you've solved in the past, particularly those related to quantitative finance or trading. Use the STAR method (Situation, Task, Action, Result) to structure your answers.