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- Tasks: Build AI-driven investment tools and forecast private equity performance.
- Company: Join a leading firm at the forefront of data science and investment.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic role with excellent career advancement in a collaborative environment.
- Why this job: Make a real impact in investment decisions using cutting-edge AI technology.
- Qualifications: 2-6 years in data science with strong Python and SQL skills.
The predicted salary is between 60000 - 80000 £ per year.
We are hiring an Associate, Data Science to help build the next generation of quantitative and AI-driven investment tools for private equity secondaries.
Role purpose
- Build models to forecast private equity performance and take them to production
- Support underwriting and portfolio decisions as a secondary investor
- Develop practical AI tools that improve investment workflows
- Champion the use of modern AI tools and AI best practice across the team
Key responsibilities
- Build quantitative, statistical and machine learning models for PE fund and asset forecasting
- Analyse proprietary and external datasets to generate investment insights
- Support live deal evaluation with data-driven analysis
- Develop AI-enabled tools for research, diligence, memo drafting and workflow automation
- Use the latest AI coding tools to accelerate development and improve code quality
- Partner with investors, engineers and data teams to productionise tools and models
- Help define best practice for AI use within the investment team
Candidate profile
- 2-6 years' experience in data science, quantitative research or machine learning
- Strong Python, SQL and statistical modelling skills
- Self-starter, innovative, strong communicator
- Experience working with messy, real-world datasets
- Ability to turn technical work into clear commercial insight
- Strong interest in investing and private markets
- Comfortable using modern AI development tools in day-to-day work
Preferred
- Experience with AI tools, and particularly AI coding tools
- Experience with forecasting, portfolio analytics or investment decision tools
- Experience building AI/LLM-based workflows
Why this role
This is a hands-on role at the intersection of investing, data science and AI. The successful candidate will help improve investment decisions and lead adoption of AI across the team.
Associate, Data Science (N0127) | London, UK employer: Coller Capital
Contact Detail:
Coller Capital Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Associate, Data Science (N0127) | London, UK
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. We can’t stress enough how important it is to make those connections; you never know who might help you land that dream job!
✨Tip Number 2
Prepare for interviews by practising common data science questions and case studies. We recommend doing mock interviews with friends or using online platforms. The more comfortable you are with your answers, the better you'll perform when it counts!
✨Tip Number 3
Showcase your skills through projects! Build a portfolio of your work, especially any AI tools or models you've developed. This gives potential employers a tangible sense of what you can do, and we all know actions speak louder than words.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to engage directly with us. So go ahead, hit that apply button!
We think you need these skills to ace Associate, Data Science (N0127) | London, UK
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Associate, Data Science role. Highlight your experience with Python, SQL, and any machine learning projects you've worked on. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and investing. Share specific examples of how you've used AI tools or built models that relate to private equity.
Showcase Your Projects: If you've worked on relevant projects, make sure to include them in your application. Whether it's a forecasting model or an AI tool, we love seeing practical applications of your skills. Don't be shy about sharing your achievements!
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It helps us keep track of applications and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Coller Capital
✨Know Your Data Science Stuff
Make sure you brush up on your Python, SQL, and statistical modelling skills. Be ready to discuss specific projects where you've built models or analysed datasets, especially in the context of private equity or investment tools.
✨Show Off Your AI Knowledge
Since this role involves developing AI tools, be prepared to talk about your experience with modern AI coding tools. Share examples of how you've used these tools to improve workflows or generate insights from messy datasets.
✨Communicate Clearly
You’ll need to turn technical jargon into clear commercial insights. Practice explaining complex concepts in simple terms, as you'll likely have to communicate with investors and team members who may not have a technical background.
✨Be a Self-Starter
Demonstrate your innovative mindset by sharing instances where you've taken initiative in past roles. Highlight any projects where you’ve championed new tools or best practices, especially in data science or investment contexts.