Who We Are At Goldman Sachs, we connect people, capital and ideas to help solve problems for our clients. We are a leading global financial services firm providing investment banking, securities and investment management services to a substantial and diversified client base that includes corporations, financial institutions, governments and individuals. Quantitative Strategists Quantitative strategists work in close collaboration with bankers, traders, and portfolio managers on complex financial and technical challenges. We work on alpha-generating strategies; discuss portfolio allocation problems; and build models for prediction, pricing, trading automation, budgeting analytics, and more. The strats platform is designed for people to express themselves by providing creative solutions to business problems. Strats own analytics, models for pricing, return and risk, as well as portfolio management platforms. Responsibilities As a quantitative strategist, your responsibilities will include: • Working with revenue-generating businesses to solve a broad range of problems, including quantitative strategy development, quantitative modelling, portfolio construction, portfolio optimization, infrastructure development and implementation, financial product and markets analytics • Develop quantitative analytics and signals using advanced statistical, quantitative, or econometric techniques to improve portfolio construction process and implement fund management models to track longer term portfolio performance • Develop sustainable production systems, which can evolve and adapt to changes in our fast-paced, global business environment • Provide quantitative analytics to optimize investment structure, pricing, returns and capital sourcing • Partner globally across multiple divisions and engineering teams to create quantitative modeling-based solutions • Prioritize competing problems and communicate with key stakeholders Basic Qualifications • Bachelor's / Master's degree in a quantitative discipline with quantitative analytics/research and financial modeling experience • Strong understanding of mathematical concepts including probability and statistics, time series analysis, regression analysis, forecasting, optimization, machine learning, and other numerical techniques • Strong fundamentals in design and analysis of algorithms and data structures • Ability to implement coding solutions to quantitative problems, experience in developing finance and statistics-based applications, and proficiency in at least one programming language such as Slang, Python, C, or C plus plus • Strong written and oral communication skills and ability to work independently and in a team environment • Ability to multi-task and prioritize work effectively • Passion and self-motivation to deliver technology solutions in a dynamic business environment Goldman Sachs Engineering Culture At Goldman Sachs, our Engineers don’t just make things – we make things possible. Change the world by connecting people and capital with ideas. 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 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? Start here!