QIS Platform Analyst

UBS · Commercial & Retail Banks · Wealth Management & Financial Advisors · Python · 1 day ago

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Salary

≈ $84k – $189k per year (Estimated)

Location

In office (New York)

Confirmed on the employer's own hiring board on Nov 3, 2026. First seen by Alion on Oct 2, 2026. UBS scores B on the Alion truth index.

Overview

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Profile match

UBS

Headquartered in Zurich, Switzerland, UBS is a leading global financial services firm and one of the world's largest wealth managers. The company provides a comprehensive range of solutions, including private banking, personal and corporate banking, asset management, and investment banking services. Operating in major financial centers across the globe, the institution assists high-net-worth individuals, corporations, and institutional clients in managing and growing their assets.

ubs.com · HQ: Zurich, Switzerland · Asset Management & Funds · Investment Banking & M&A Advisory · Wealth Management & Financial Advisors · Commercial & Retail Banks · 5000+ employees · Est. 1998

Tech stack of UBS

Backed by Blue Lion

Investment Bank

Are you excited by the opportunity to build and own production-grade Python solutions that power a strategic front office platform? Do you enjoy solving complex problems across technology, data, and business domains? Are you interested in applying AI at scale to improve platform performance, monitoring, and automation?

We are looking for a QIS Platform Analyst to:

design, develop, and maintain production-grade Python applications that support platform analytics, controls, monitoring, workflow automation, and business-critical processes
build scalable and resilient data pipelines, validation frameworks, and analytical services used in live production environments, applying strong software engineering practices including testing, code reviews, documentation, and maintainability
use Python to develop AI and machine learning capabilities, including intelligent monitoring, anomaly detection, signal identification, and automated control processes
enhance platform resilience through automated checks, dashboards, observability frameworks, and proactive investigation and resolution of production issues
solve complex problems across systems, data, processes, and business logic while driving long-term, scalable improvements rather than short-term fixes

• partner closely with Trading, Structuring, Model Quants, and Technology teams to deliver robust solutions, support platform evolution, and onboard new strategies, datasets, and capabilities

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