At a Glance
- Tasks: Join a dynamic team to analyze unstructured data and drive insights for investment decisions.
- Company: A global private equity firm supporting ambitious entrepreneurs and high-growth companies.
- Benefits: Competitive salary, bonus structure, and hybrid work in Central London.
- Why this job: Combine cutting-edge AI with impactful financial applications in a fast-paced environment.
- Qualifications: Extensive NLP and Python experience, SQL knowledge, and a degree in a STEM field.
- Other info: Opportunity to shape strategic decisions in a well-known investment firm.
The predicted salary is between 80000 - 90000 £ per year.
Data Scientist – Private Equity
- Paying between £80,000-£90,000 + 12-15% bonus (written in contract)
- Hybrid in Central London
- Well Known PE-firm
- Python/NLP
I am currently working with a Global Private-equity firm, who are looking for a talented mid/snr Data Scientist to join their team to focus on due-diligence and deals.
This company is an international investment firm that supports the most ambitious and talented entrepreneurs and high growth companies to achieve their goals. They invest in high growth, dynamic situation buyouts and growth capital investments.
This role focuses on applying advanced NLP models to analyse unstructured data from diverse sources, driving actionable insights into market opportunities and company performance. These insights will play a critical role in deal sourcing, due diligence, and portfolio management, shaping the fund’s strategic decisions.
If you’re passionate about combining cutting-edge AI with high-impact financial applications, then this will be a great opportunity for you – here are the requirements:
- Extensive NLP & Python experience
- Experience with SQL and cloud computing – GCP preferred but Azure and AWS if fine.
- Knowledge of DBT/Data Engineering is a bonus,
- Degree + in a STEM field
If you’re interested in this role and feel you fit some of the requirements, apply through the AD to find out more!
Data Scientist – Private Equity
Data Scientist – Private Equity employer: La Fosse
Contact Detail:
La Fosse Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist – Private Equity
✨Tip Number 1
Make sure to showcase your experience with NLP and Python in your conversations. Be ready to discuss specific projects where you've applied these skills, especially in a financial context.
✨Tip Number 2
Familiarize yourself with the private equity landscape and current market trends. Being able to discuss recent deals or market movements can demonstrate your genuine interest in the field.
✨Tip Number 3
Prepare to explain how you would approach analyzing unstructured data. Think about methodologies you would use and be ready to share examples of how you've derived insights from similar data sets.
✨Tip Number 4
Network with professionals in the private equity space. Attend relevant meetups or webinars to connect with industry insiders who might provide valuable insights or referrals.
We think you need these skills to ace Data Scientist – Private Equity
Some tips for your application 🫡
Highlight Relevant Experience: Make sure to emphasize your extensive experience with NLP and Python in your CV and cover letter. Provide specific examples of projects where you've applied these skills, especially in financial contexts.
Showcase Your Technical Skills: Detail your proficiency with SQL and cloud computing platforms like GCP, Azure, or AWS. Mention any relevant certifications or projects that demonstrate your technical capabilities.
Tailor Your Application: Customize your CV and cover letter to align with the job description. Use keywords from the listing, such as 'due diligence', 'market opportunities', and 'portfolio management' to make your application stand out.
Express Your Passion: In your cover letter, convey your enthusiasm for combining AI with financial applications. Share why this role excites you and how you can contribute to the firm's strategic decisions.
How to prepare for a job interview at La Fosse
✨Showcase Your NLP Expertise
Be prepared to discuss your experience with Natural Language Processing in detail. Highlight specific projects where you've applied advanced NLP models, and be ready to explain the methodologies you used and the insights you derived from unstructured data.
✨Demonstrate Your Python Skills
Since Python is a key requirement for this role, make sure to discuss your proficiency with it. Bring examples of how you've utilized Python in data analysis or model development, and be ready to solve a coding challenge during the interview.
✨Understand the Financial Context
Familiarize yourself with the private equity landscape and how data science plays a role in deal sourcing and due diligence. Being able to connect your technical skills to financial applications will show that you understand the business impact of your work.
✨Prepare Questions About the Company
Research the firm and prepare insightful questions about their investment strategies and how they leverage data science. This shows your genuine interest in the company and helps you assess if it's the right fit for you.