GM Distribution - Quantitative Analyst/Engineer
About The Position
UBS is hiring a Quantitative Engineer for its Quant Analytics team in Global Markets Distribution, based in New York City. The team is a Centre of Excellence that works directly with the sales and trading desks it supports. It is a small, informal group spanning AI, analytics, and engineering, with modern tooling within the bank’s governance framework and the opportunity to help shape the team as it grows. The role combines hands-on engineering with team leadership. The Quantitative Engineer will build and operate analytics and AI services end to end, addressing real Distribution problems by assessing data, selecting appropriate techniques, and putting production solutions in front of users. The work includes owning implementation, data quality, monitoring, cost, and releases, while partnering closely with sales and trading desks, quants, and developers. UBS is open to applications from career returners.
Requirements
- A four-year degree in mathematics, computer science, engineering, or a related field.
- Experience as a team lead or manager while remaining a hands-on Quantitative Engineer, providing technical leadership, supporting team development, and delivering production solutions.
- Strong Python skills and production engineering practices, including testing, version control, code review, and sound software architecture.
- Hands-on experience with modern AI tooling, including LLM-based and agentic applications.
- Solid data engineering experience with large, complex financial datasets.
- Confidence working with cloud and containerized deployments.
- Knowledge of Global Markets and sales workflows, or the ability to learn quickly by working closely with the desk.
- Clear, concise communication, sound judgment, and a practical approach to unfamiliar business problems.
- Curiosity about using AI to improve the building, delivery, and optimization of workflows, with sound judgment in validating outputs and aligning with policies, risk standards, and ethical use.
Nice To Haves
- A master’s degree.
- Experience with Kubernetes, Apache Airflow, Microsoft Azure, Apache Spark, and kdb+/q; these are welcome but not required.
Responsibilities
- Lead or work with a team while remaining a hands-on engineer, owning implementation, data quality, monitoring, cost, and releases.
- Solve Distribution problems by assessing data, selecting an appropriate approach, building solutions, and delivering them to users.
- Design, build, and operate analytics and AI services end to end, from data and models through to user-facing tools.
- Partner directly with sales and trading desks, quants, and developers to frame problems and deliver working solutions.
- Choose suitable techniques for each problem and reuse existing solutions when appropriate.
- Raise engineering standards and help grow the team.
- Provide technical leadership, support team development, and deliver production solutions.
Benefits
- UBS offers competitive benefits.
- Flexible working options when possible.
- Opportunities to grow.
- A supportive team.
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What This Job Offers
Job Type
Full-time
Career Level
Manager
