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- Tasks: Enhance investment processes using advanced analytics and quantitative methods.
- Company: Leading global investment firm with a focus on innovation.
- Benefits: Competitive benefits and dynamic work environment.
- Why this job: Make a significant impact in Private Equity Data Science.
- Qualifications: PhD in a quantitative field and strong programming skills required.
- Other info: Collaborate with Deal Teams for real business value.
The predicted salary is between 36000 - 60000 £ per year.
A leading global investment firm is seeking a Data Scientist to enhance the Private Equity Data Science team. The ideal candidate will leverage their expertise in quantitative methods and data-driven models to optimize investment processes.
Responsibilities include:
- Partnering with Deal Teams
- Implementing advanced analytics to drive significant business value
A PhD in a quantitative field and strong programming skills (Python, SQL) are essential. This role offers competitive benefits and the opportunity to work in a dynamic environment.
Quantitative Engineering Associate - PE Data Science in London employer: Goldman Sachs Bank AG
Contact Detail:
Goldman Sachs Bank AG Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Engineering Associate - PE Data Science in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the investment and data science fields on LinkedIn. A friendly message can go a long way in getting your foot in the door.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your quantitative methods and data-driven models. This will help you stand out and demonstrate your expertise during interviews.
✨Tip Number 3
Practice makes perfect! Brush up on your programming skills, especially in Python and SQL. Consider working on real-world projects or challenges to keep your skills sharp.
✨Tip Number 4
Apply through our website! We make it easy for you to find roles that match your skills. Plus, it shows you're genuinely interested in joining our team.
We think you need these skills to ace Quantitative Engineering Associate - PE Data Science in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your quantitative skills and programming expertise. We want to see how your experience aligns with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about data science in private equity and how you can add value to our team. Keep it concise but impactful!
Showcase Your Technical Skills: Since strong programming skills in Python and SQL are essential, make sure to mention any relevant projects or experiences where you’ve used these languages. We love seeing practical applications of your skills!
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 Goldman Sachs Bank AG
✨Know Your Quantitative Stuff
Make sure you brush up on your quantitative methods and data-driven models. Be ready to discuss how you've applied these in past projects, especially in investment processes. This will show that you can hit the ground running!
✨Show Off Your Programming Skills
Since strong programming skills in Python and SQL are essential, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice common data manipulation tasks and algorithms beforehand.
✨Understand the Business Side
It's not just about the numbers! Familiarise yourself with how private equity works and the specific challenges faced by Deal Teams. This knowledge will help you articulate how your analytics can drive business value.
✨Ask Insightful Questions
Prepare thoughtful questions that show your interest in the role and the company. Inquire about the team’s current projects or the tools they use for analytics. This demonstrates your enthusiasm and helps you gauge if it’s the right fit for you.
