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- Tasks: Join our Private Equity Data Science team to innovate with AI and quantitative models.
- Company: Goldman Sachs, a leading global investment banking and management firm.
- Benefits: Competitive salary, generous vacation, health insurance, and wellness programs.
- Why this job: Make a real impact in finance using cutting-edge data science techniques.
- Qualifications: PhD or equivalent in a quantitative field and strong programming skills.
- Other info: Dynamic work environment with excellent growth opportunities and commitment to diversity.
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 realised commercial impact.
- Excellent written and verbal communication and collaboration skills with a strong growth mindset.
At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world.
We believe who you are makes you better at what you do. We’re committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs.
Asset & Wealth Management - Quantitative Engineering - Associate - London London · United Kingd[...] employer: Goldman Sachs Bank AG
Contact Detail:
Goldman Sachs Bank AG Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Asset & Wealth Management - Quantitative Engineering - Associate - London London · United Kingd[...]
✨Tip Number 1
Network like a pro! Reach out to current employees at Goldman Sachs or in the Asset & Wealth Management sector. A friendly chat can give you insider info and maybe even a referral.
✨Tip Number 2
Prepare for interviews by brushing up on your quantitative skills. Be ready to discuss your experience with Python, SQL, and data science libraries. Show them you can turn complex data into actionable insights!
✨Tip Number 3
Don’t just apply; engage! When you submit your application through our website, follow up with a personalised message expressing your enthusiasm for the role. It shows initiative and can set you apart.
✨Tip Number 4
Stay updated on the latest trends in AI and ML. Being knowledgeable about current developments will not only impress interviewers but also help you contribute meaningfully to the team.
We think you need these skills to ace Asset & Wealth Management - Quantitative Engineering - Associate - London London · United Kingd[...]
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the role. Highlight your relevant experience in quantitative methods and data science, and show how your skills align with what we’re looking for at StudySmarter.
Showcase Your Skills: Don’t just list your programming skills; demonstrate them! Include specific examples of projects where you’ve used Python or SQL to solve complex problems. We want to see how you can apply your knowledge in real-world scenarios.
Be Clear and Concise: When writing your application, clarity is key. Use straightforward language and avoid jargon unless it’s necessary. We appreciate well-structured applications that get straight to the point while showcasing your expertise.
Apply Through Our Website: We encourage you to submit your application through our website. It’s the best way to ensure your application gets seen by the right people. Plus, you’ll find all the details you need about the role and our company culture there!
How to prepare for a job interview at Goldman Sachs Bank AG
✨Know Your Quantitative Stuff
Make sure you brush up on your quantitative skills, especially in statistics and programming. Be ready to discuss how you've applied these skills in real-world scenarios, particularly in investment processes or data-driven models.
✨Showcase Your Programming Skills
Familiarise yourself with Python and SQL, as well as the data science libraries like pandas and scikit-learn. Prepare to demonstrate your coding abilities, perhaps by solving a problem or discussing a project where you used these tools effectively.
✨Understand the Business Context
It's crucial to connect your technical expertise with commercial outcomes. Think about how your analyses have driven value in previous roles and be prepared to share specific examples that highlight your impact on investment performance.
✨Communicate Clearly and Confidently
Strong communication skills are key in this role. Practice explaining complex data insights in simple terms, as you'll need to collaborate with various teams. Be ready to discuss how you've worked with others to achieve common goals in past projects.
