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For Companies At a Glance
- 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 a supportive work environment.
- Why this job: Make a real impact using AI and data science in the finance world.
- Qualifications: PhD or equivalent in a quantitative field and strong programming skills required.
- Other info: Collaborative culture with excellent career advancement opportunities.
The predicted salary is between 43200 - 72000 £ 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.
About Goldman Sachs: 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. Learn more about our culture, benefits, and people at GS.com/careers.
We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process.
Asset & Wealth Management - Quantitative Engineering - Associate - London employer: WeAreTechWomen
Contact Detail:
WeAreTechWomen 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
Show off your skills! Prepare a portfolio or a project that highlights your quantitative and programming prowess. This is your chance to demonstrate how you can add value to the team.
✨Tip Number 3
Ace the interview by being ready to discuss real-world applications of your work. Think about how your past experiences can translate into success for the Private Equity Data Science team.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're serious about joining the team.
We think you need these skills to ace Asset & Wealth Management - Quantitative Engineering - Associate - London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your programming skills and experience with data science libraries like pandas and scikit-learn. We want to see how you can leverage these tools to tackle complex datasets and drive commercial value.
Tailor Your Application: Don’t just send a generic application! Tailor your CV and cover letter to reflect the specific responsibilities and qualifications mentioned in the job description. Show us how your background aligns with what we’re looking for.
Be Clear and Concise: When writing your application, clarity is key. Use straightforward language to explain your experiences and achievements. We appreciate well-structured applications that get straight to the point!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our team!
How to prepare for a job interview at WeAreTechWomen
✨Know Your Data Science Stuff
Make sure you brush up on your quantitative methods and data science techniques. Be ready to discuss how you've applied these skills in real-world scenarios, especially in investment processes. Prepare examples that showcase your programming prowess in Python and SQL, as well as your experience with libraries like pandas and scikit-learn.
✨Understand the Business Context
It's crucial to connect your technical skills to the commercial impact they can have. Research Goldman Sachs' approach to private equity and think about how your work can drive value creation. Be prepared to discuss how you've translated complex data into actionable insights that have influenced business decisions.
✨Communicate Clearly
Strong communication skills are key in this role. Practice explaining your analyses and findings in a way that's easy to understand, even for those who might not have a technical background. Think about how you can convey complex ideas succinctly and effectively during the interview.
✨Stay Current with Trends
Show your enthusiasm for the field by staying updated on the latest developments in AI and machine learning. Be ready to discuss recent advancements and how they could be applied to enhance investment processes. This demonstrates your commitment to continuous improvement and innovation in your work.
