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- Tasks: Develop advanced analytics solutions for data-driven investment decisions.
- Company: Globally recognised private equity firm in London.
- Benefits: Salary up to £100,000 and collaboration with senior stakeholders.
- Why this job: Join a fast-paced environment prioritising data science in investments.
- Qualifications: 4+ years in data science and strong Python skills required.
- Other info: Opportunity to work with complex datasets and drive impactful decisions.
The predicted salary is between 60000 - 84000 £ per year.
A globally recognised private equity firm is seeking a Data Scientist to join their team in London. You will develop advanced analytics solutions to support data-driven investment decisions.
The ideal candidate should have:
- At least 4 years in data science
- Strong Python skills
- The ability to analyze complex datasets
This role offers a salary up to £100,000 and requires collaboration with senior stakeholders in a fast-paced environment that prioritises data science in the investment process.
Senior Data Scientist - Private Equity, Deal Team (London) employer: Jobster
Contact Detail:
Jobster Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist - Private Equity, Deal Team (London)
✨Tip Number 1
Network like a pro! Reach out to current or former employees of the firm on LinkedIn. A friendly chat can give us insider info and might just get your foot in the door.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your data science projects, especially those involving Python and complex datasets. This will help us demonstrate our expertise during interviews.
✨Tip Number 3
Practice makes perfect! Get ready for technical interviews by brushing up on data science concepts and coding challenges. We can even set up mock interviews with friends to build confidence.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we often have exclusive roles listed there that you won’t find anywhere else.
We think you need these skills to ace Senior Data Scientist - Private Equity, Deal Team (London)
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your Python skills and any relevant data science experience in your application. We want to see how you can analyse complex datasets and develop advanced analytics solutions.
Tailor Your Application: Don’t just send a generic CV! Tailor your application to the job description, focusing on your experience that aligns with the role. We love seeing candidates who take the time to connect their background with what we’re looking for.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured applications that make it easy for us to see your qualifications and fit for the role.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to track your application and ensure it reaches the right people!
How to prepare for a job interview at Jobster
✨Know Your Data Science Fundamentals
Brush up on your data science fundamentals, especially in Python and analytics. Be prepared to discuss your previous projects and how you used data to drive investment decisions. This will show your depth of knowledge and practical experience.
✨Showcase Your Problem-Solving Skills
Prepare to tackle case studies or hypothetical scenarios during the interview. Think about how you would approach complex datasets and what analytical methods you would apply. This demonstrates your critical thinking and problem-solving abilities.
✨Understand the Private Equity Landscape
Familiarise yourself with the private equity sector and current market trends. Being able to discuss how data science can influence investment strategies will impress the interviewers and show that you’re genuinely interested in the role.
✨Engage with Stakeholders
Since this role involves collaboration with senior stakeholders, practice articulating your ideas clearly and confidently. Prepare questions that reflect your understanding of their needs and how your skills can contribute to their goals.
