At a Glance
- Tasks: Tackle challenging engineering problems and drive AI/ML adoption in finance.
- Company: Goldman Sachs, a leading global investment firm with a focus on innovation.
- Benefits: Diverse opportunities for growth, wellness programs, and a commitment to inclusion.
- Other info: Collaborative environment with excellent career advancement opportunities.
- Why this job: Join a dynamic team redefining AI possibilities in finance and make a real impact.
- Qualifications: Experience in Python applications and AI/ML, with a relevant degree or industry experience.
Solve the most challenging and pressing engineering problems for our clients. Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action. Create new businesses, transform finance, and explore a world of opportunity at the speed of markets.Engineering, which is comprised of our Technology Division and global strategist groups, is at the critical center of our business, and our dynamic environment requires innovative strategic thinking and immediate, real solutions. Want to push the limit of digital possibilities? Who We Look ForGoldman Sachs is seeking an Applied AI Researcher to join our dynamic Applied Artificial Intelligence (AI) Research team. As an integral part of the team, you will play a pivotal role in driving the adoption of cutting-edge AI and Machine Learning (ML) technologies at the firm.In this role, you will have the opportunity to contribute to various AI/ML domains, including but not limited to machine learning, deep learning, natural language processing, information retrieval, time series analysis, and recommender systems. As an experienced AI Researcher, you will help address the unique challenges that arise in machine learning systems within the financial domain. Join us in redefining the boundaries of what's possible in the intersection of quantitative research and artificial intelligence!Collaborating effectively with colleagues to advance production machine-learning systems and applications.Conceptualizing, experimenting with, and assessing AI/ML-based software systems.Developing, testing, and maintaining high-quality, production-ready code.Demonstrating technical leadership by taking charge of cross-team projects.Represent Goldman Sachs at conferences and within open-source communities.Required Qualifications:Strong hands-on experience building and maintaining large-scale Python applications. D. degree in Computer Science, Machine Learning, Mathematics, Statistics, Physics, Engineering, Quantitative Finance, or equivalent relevant industry experience.A minimum of 1-3 years of AI/ML experience in the industry that demonstrates your expertise.Extensive experience in software development for quantitative investment workflows in equities, fixed income, or multi-asset strategies.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'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. We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.
Research Associate - Artificial Social Intelligence in London employer: Goldman Sachs
Goldman Sachs is an exceptional employer, offering a dynamic work environment in the heart of London where innovation and collaboration thrive. Employees benefit from comprehensive professional development opportunities, a strong emphasis on diversity and inclusion, and the chance to work with some of the brightest minds in finance. With a commitment to client success and a culture that fosters growth, joining Goldman Sachs means being part of a prestigious firm that values your contributions and supports your career aspirations.
StudySmarter Expert Advice🤫
We think this is how you could land Research Associate - Artificial Social Intelligence in London
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We think you need these skills to ace Research Associate - Artificial Social Intelligence in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Craft a Tailored Cover Letter:For a full-time role at Goldman Sachs, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Goldman Sachs. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Goldman Sachs
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Goldman Sachs!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
