At a Glance
- Tasks: Conduct quantitative research and develop AI-driven investment strategies.
- Company: Join Orchid AI, a leader in AI-native asset management.
- Benefits: Flexible remote work, competitive pay, and career growth opportunities.
- Other info: Collaborate with experts and access cutting-edge tools.
- Why this job: Make an impact at the forefront of AI and finance.
- Qualifications: Strong quantitative skills and programming experience in Python.
The predicted salary is between 60000 - 80000 £ per year.
Orchid AI is building an AI-native asset management platform that combines quantitative research, machine learning, agentic AI systems, and alternative data to generate differentiated investment insights and systematic investment strategies. Our mission is to create a modern research and portfolio management stack where human expertise and AI work together to discover, validate, and scale alpha opportunities across global markets.
We are seeking a highly motivated Quantitative Researcher to join our investment research team. This role offers the opportunity to work across the full investment research lifecycle, from idea generation and data acquisition through signal development, portfolio construction, backtesting, and live strategy monitoring.
You will work closely with portfolio managers, AI engineers, and data scientists to develop systematic investment strategies powered by alternative data, machine learning, and agentic AI workflows. The ideal candidate combines strong quantitative skills with a deep curiosity about financial markets and emerging AI technologies.
Location: Flexible / Remote (with preference for overlap with U.S. and European market hours)
Key Responsibilities:
- Conduct quantitative research to identify and develop alpha-generating investment signals across equities and other liquid asset classes.
- Design, test, and refine systematic investment strategies using statistical, machine learning, and AI-driven approaches.
- Source, evaluate, and integrate alternative, fundamental, macroeconomic, and market data into research pipelines.
- Develop robust back testing frameworks and research infrastructure to evaluate strategy performance and risk characteristics.
- Apply modern AI and agentic systems to automate research workflows, data analysis, idea generation, and portfolio monitoring.
- Collaborate with portfolio managers to translate research insights into investable strategies and portfolio construction frameworks.
- Build predictive models for forecasting returns, risk, market regimes, and factor behavior across varying time horizons.
- Monitor live strategies and continuously improve models based on changing market conditions and new data sources.
- Contribute to the development of Orchid AI’s proprietary investment intelligence platform and research ecosystem.
- Communicate research findings clearly through written reports, presentations, and collaborative discussions.
Required Qualifications:
- Bachelor's, Master's, or PhD in Mathematics, Statistics, Computer Science, Physics, Engineering, Economics, Finance, or a related quantitative discipline.
- Strong programming skills in Python and experience with quantitative research libraries and data science tools.
- Strong foundation in statistics, probability, optimization, machine learning, and financial modeling.
- Experience working with large structured and unstructured datasets.
- Ability to independently formulate hypotheses, design experiments, and evaluate results rigorously.
- Strong communication skills and the ability to explain complex quantitative concepts to both technical and investment audiences.
Preferred Experience:
- 3+ years of experience in quantitative research, systematic investing, hedge funds, asset management, proprietary trading, or fintech.
- Experience developing alpha signals, factor models, forecasting systems, or portfolio optimization frameworks.
- Experience with alternative datasets, including corporate, consumer, geospatial, web, transaction, or other non-traditional data sources.
- Experience building research platforms, data pipelines, or production-grade quantitative infrastructure.
- Familiarity with cloud computing environments and modern data engineering practices.
- Experience applying machine learning, large language models (LLMs), or agentic AI systems to investment research and decision-making.
Highly Valued Experience:
- Building proprietary datasets or investment intelligence products.
- Research involving cross-sectional equity selection, statistical arbitrage, factor investing, or multi-asset strategies.
- Experience integrating heterogeneous data sources into unified predictive frameworks.
- Developing AI agents for research automation, knowledge extraction, market intelligence, or portfolio management workflows.
- Working in entrepreneurial, fast-moving investment or technology environments.
- Experience taking research from concept to live deployment and ongoing performance management.
Why Join Orchid AI?
- Build at the intersection of AI, quantitative finance, and asset management.
- Work directly with founders and senior investment professionals.
- Access cutting-edge AI tools, alternative datasets, and research infrastructure.
- Significant opportunity for ownership, impact, and career growth.
- Competitive compensation, performance incentives, and equity participation for exceptional candidates.
Quantitative Researcher in London employer: Orchid AI
Orchid AI is an exceptional employer that offers a unique opportunity to work at the forefront of AI and quantitative finance. With a flexible remote work environment, employees benefit from collaboration with industry leaders, access to cutting-edge tools, and significant opportunities for personal and professional growth. The company fosters a culture of innovation and impact, ensuring that every team member can contribute meaningfully to the development of advanced investment strategies.
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative Researcher in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the finance and AI sectors on LinkedIn. Join relevant groups, attend webinars, and don’t be shy about asking for informational interviews. We all know that sometimes it’s not just what you know, but who you know!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your quantitative research projects, especially those involving machine learning or alternative data. This will give potential employers a taste of what you can do and how you think. We love seeing creativity and initiative!
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and market knowledge. Be ready to discuss your past projects and how they relate to the role at Orchid AI. We want to see your passion for finance and AI shine through!
✨Tip Number 4
Apply directly through our website! It’s the best way to ensure your application gets seen. Plus, we’re always on the lookout for candidates who take the initiative. Let’s make it happen together!
We think you need these skills to ace Quantitative Researcher in London
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your quantitative skills and programming experience in Python. We want to see how you can apply these skills to the investment research lifecycle, so don’t hold back!
Be Curious:We love candidates who are genuinely curious about financial markets and AI technologies. Share your thoughts on recent trends or innovations in your application to show us your passion!
Tailor Your Application:Don’t just send a generic application! Tailor your CV and cover letter to reflect the specific responsibilities and qualifications mentioned in the job description. It’ll make a big difference.
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’s super easy!
How to prepare for a job interview at Orchid AI
✨Know Your Quantitative Stuff
Brush up on your quantitative skills and be ready to discuss your experience with statistical methods, machine learning, and financial modelling. Prepare examples of how you've applied these skills in past projects or roles, especially in developing alpha signals or investment strategies.
✨Show Your Curiosity
Demonstrate your curiosity about financial markets and emerging AI technologies. Be prepared to discuss recent trends in the industry, alternative data sources, and how they can impact investment strategies. This shows you're not just knowledgeable but also passionate about the field.
✨Communicate Clearly
Practice explaining complex quantitative concepts in simple terms. You might need to present your research findings or collaborate with portfolio managers who may not have a technical background. Clear communication can set you apart from other candidates.
✨Prepare for Technical Questions
Expect technical questions related to programming in Python, working with large datasets, and building predictive models. Brush up on your coding skills and be ready to solve problems on the spot. Familiarity with quantitative research libraries will definitely give you an edge.
