Multi Asset Solutions Digital Strategist Analyst

Multi Asset Solutions Digital Strategist Analyst at Goldman Sachs

Who We Are

The Multi Asset Solutions (MAS) Digital Strats team at Goldman Sachs takes a hands-on approach to ideate, design, and implement full-stack solutions for portfolio managers, sales teams, and clients. Our primary objectives are to drive revenue growth through the development of sophisticated tools for portfolio construction and client engagement, while also delivering scalable and efficient systems for portfolio management. We design, build, and maintain every layer of our technology stack—including databases, data caching, calculation engines, workflow orchestration, and front-end tooling—and leverage advanced quantitative models to decompose multi-asset portfolios from both top-down and bottom-up perspectives. Increasingly, we are integrating AI and agent-based tools to provide intuitive, flexible solutions and drive efficiency for stakeholders. This role is ideal for individuals with a keen interest in understanding business problems and expanding their technical skillsets.

What You Do

• Develop and maintain proprietary infrastructure, libraries and APIs that provide quantitative portfolio analytics and data insights.
• Collaborate with colleagues to design and implement full-stack solutions for portfolio managers and sales teams, including dashboard and reporting tools.
• Work closely with stakeholders to understand requirements and contribute to impactful solutions that drive revenue growth.
• Develop AI and agent-based technologies to enhance user experience and operational efficiency.
• Utilize Machine Learning techniques to derive actionable insights from client and CRM datasets.
• Ensure production systems are sustainable, adaptable, and resilient in a dynamic business environment.
• Learn and apply quantitative models to decompose multi-asset portfolios from both top-down and bottom-up perspectives.

What We Look For

• 0-3 years of experience in quantitative or technical fields, with demonstrated interest in financial technology.
• Technical degree in Computer Science, Mathematics, Engineering, or a related field.
• Proficiency in programming languages such as TypeScript, JavaScript, and/or Python.
• Familiarity with databases (SQL, MongoDB), data caching, and workflow orchestration concepts.
• Some knowledge of modern DevOps practices and tools such as Kubernetes.
• Interest in quantitative modeling, portfolio theory, portfolio construction, and risk analytics.
• Eagerness to work across the full technology stack, from databases and infrastructure to user interfaces.
• Strong communication skills, with the ability to collaborate with global teams and stakeholders.
• Self-motivated, curious problem-solver with a passion for learning and innovation in financial technology.

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.

Salary Range

The expected base salary for this New York, New York, United States-based position is $110,000-$130,000. In addition, you may be eligible for a discretionary bonus if you are an active employee as of fiscal year-end.

Benefits

Goldman Sachs is committed to providing our people with valuable and competitive benefits and wellness offerings, as it is a core part of providing a strong overall employee experience. A summary of these offerings, which are generally available to active, non-temporary, full-time and part-time US employees who work at least 20 hours per week, can be found here.

Key skills/competency

• Quantitative Analysis
• Full-Stack Development
• Portfolio Construction
• Machine Learning
• AI/Agent-Based Tools
• TypeScript
• Python
• SQL
• DevOps
• Risk Analytics
• Data Insights