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- Tasks: Join our team to design and implement data-driven models for investment processes.
- Company: Goldman Sachs, a leading global investment banking and management firm.
- Benefits: Diverse opportunities for growth, wellness programs, and competitive benefits.
- Why this job: Make a real impact in finance using cutting-edge AI and data science.
- Qualifications: PhD in a quantitative field and strong programming skills required.
- Other info: Collaborative environment with a focus on diversity and inclusion.
The predicted salary is between 36000 - 60000 £ per year.
Join our Private Equity Data Science team and contribute to DSML and AI initiatives across the full lifecycle of the investment process. The Data Scientist will be responsible for the design, development, and implementation of quantitative and data-driven models to drive innovation and productivity for origination, due diligence, and investment performance. The data science team sits alongside the Goldman Sachs Private Equity Deal Teams and works closely with the Goldman Sachs Value Accelerator and portfolio company management teams.
Key Responsibilities
- Leverage sophisticated statistical, mathematical, and programming skills to analyse complex datasets, support the investment processes, and drive quantifiable commercial value.
- Partner with Deal Teams to define and deliver data-driven origination initiatives.
- Deliver quantitative analyses through investment due diligence; translating complex data into comprehensive analyses assessing potential risk and opportunities in tight timelines.
- Partner strategically with portfolio company management teams to drive data and AI initiatives for value creation.
- Partner with GS Engineering to lead development and implementation of data-centric tools, enhancing our investment processes and supporting our deal and fundraising teams.
- Stay up-to-date with the latest developments in AI, ML, and related fields to continuously improve the division's AI capabilities.
Qualifications, Experience, and Attributes
- PhD or equivalent in a quantitative field such as Mathematics, Computer Science, Physics or in a related field.
- 2+ years of relevant experience applying quantitative methods to commercial problems.
- Strong programming skills (Python, SQL) and experience using the basic data science libraries (e.g. pandas, scikit-learn).
- High-level of proficiency in mathematics, statistics, and data science theory.
- Proven experience implementing sophisticated data science techniques, handling large datasets, translating data into actionable business insights.
- Commercial experience with a strong track record of quantitative problem solving and realized commercial impact.
- Excellent written and verbal communication and collaboration skills with a strong growth mindset.
Asset & Wealth Management - Quantitative Engineering -Associate - London employer: Goldman Sachs
Contact Detail:
Goldman Sachs Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Asset & Wealth Management - Quantitative Engineering -Associate - London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Goldman Sachs. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Prepare for interviews by brushing up on your quantitative skills. Be ready to discuss how you've used Python and SQL in real-world scenarios. Show them you can turn complex data into actionable insights!
✨Tip Number 3
Stay updated on the latest trends in AI and data science. Bring fresh ideas to the table during interviews. They want to see that you're not just a number cruncher but also a forward-thinker!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're serious about joining the team at Goldman Sachs.
We think you need these skills to ace Asset & Wealth Management - Quantitative Engineering -Associate - London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role. Highlight your quantitative skills and relevant experience in data science, especially any work with AI or ML. We want to see how your background aligns with what we do!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about asset and wealth management and how your skills can contribute to our team. Keep it concise but impactful!
Showcase Your Projects: If you've worked on any relevant projects, make sure to mention them! Whether it's a personal project or something from your previous job, we love to see how you've applied your skills in real-world scenarios.
Apply Through Our Website: Don't forget to apply 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 to navigate!
How to prepare for a job interview at Goldman Sachs
✨Know Your Data Science Stuff
Make sure you brush up on your quantitative methods and data science theories. Be ready to discuss how you've applied these skills in real-world scenarios, especially in investment processes. They’ll want to see that you can translate complex data into actionable insights.
✨Show Off Your Programming Skills
Since strong programming skills in Python and SQL are crucial for this role, be prepared to talk about specific projects where you've used these languages. Maybe even bring along a portfolio of your work or examples of data-driven models you've developed.
✨Understand the Business Side
It’s not just about the numbers! Make sure you can articulate how your quantitative analyses have led to commercial value. Think of examples where your insights have directly impacted investment decisions or risk assessments.
✨Stay Current with AI Trends
They’re looking for someone who’s up-to-date with the latest in AI and ML. Do some research on recent advancements in these fields and be ready to discuss how they could apply to the role. Showing that you’re proactive about learning will definitely impress them!
