UBS

QIS Platform Analyst

UBS$90K — $130K *
Finance & Insurance
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Strong Python skills with experience delivering production-grade solutions
  • Hands-on experience with AI or machine learning in production or advanced prototyping
  • Experience with modern data platforms, cloud, or distributed systems
  • Strong data analysis and problem-solving abilities in complex environments
  • Ability to work across technical and business domains with an ownership mindset
  • Experience in building monitoring, observability, or automation frameworks
  • Familiarity with systematic strategies, quantitative finance, or front office platforms

Responsibilities

  • Design, develop and maintain production-quality Python code for QIS platform analytics
  • Build scalable and resilient data pipelines used in live environments
  • Contribute to AI and ML initiatives including intelligent monitoring and anomaly detection
  • Lead investigations into data or production anomalies and drive resolution
  • Support onboarding of new strategies, features, and datasets
  • Translate business problems into robust technical solutions for senior stakeholders
  • Continuously improve platform resilience and scalability

Benefits

  • High visibility and significant autonomy
  • Opportunity to apply AI in real production environments
  • Multi-disciplinary role requiring diverse problem-solving skills
  • Direct interaction with senior stakeholders across various teams
  • Work within a strategic platform supporting Quantitative Investment Solutions
Full Job Description
Your role

Are you interested in a role that offers high visibility, significant autonomy, and the opportunity to apply AI in real production environments within a front office adjacent setting?

As a QIS Platform Analyst, you will operate at the intersection of Python engineering, data, AI and front office processes, with direct ownership of platform analytics, intelligent monitoring and automation capabilities. The role is deliberately multi disciplinary, requiring the ability to handle a broad spectrum of problems spanning technology, data, business logic and controls.
This role offers high visibility, significant autonomy, and the opportunity to apply AI in real production environments within a front office adjacent setting.

Key responsibilities:
Python engineering (core responsibility)
o Design, develop and maintain production quality Python code supporting QIS platform analytics, controls, monitoring and workflow automation
o Build scalable, resilient data pipelines and validation frameworks used in live environments
o Apply strong software engineering discipline: testing, code review, documentation and maintainability
• AI & machine learning
o Contribute directly to AI / ML initiatives across the QIS platform, including intelligent monitoring, anomaly detection, signal identification, and automation of control processes
o Work with both structured and unstructured datasets to enable AI driven platform capabilities
o Partner with quants, data scientists and engineers to industrialise AI concepts from prototype into production
• Platform monitoring & resilience
o Design and enhance automated checks, dashboards and observability frameworks
o Lead investigations into data or production anomalies and drive resolution across teams
o Continuously improve platform resilience, transparency and scalability
• Multi disciplinary problem solving
o Handle a plethora of disciplines simultaneously: coding, data analysis, platform design, process optimisation and stakeholder coordination
o Break down complex, ambiguous problems spanning systems, data and business logic
o Drive durable, structural improvements rather than short term fixes
• Change & platform evolution
o Support onboarding of new strategies, features, datasets and analytical capabilities
o Contribute to re platforming and modernisation initiatives
o Identify opportunities to improve automation, developer tooling and operational efficiency
• Stakeholder engagement
o Work closely with Trading, Structuring, Model Quants and Technology teams
o Translate business problems into robust technical solutions and communicate outcomes clearly to senior stakeholders

Your team

The QIS Platform team builds and operates the strategic platform supporting Quantitative Investment Solutions across Global Markets. It enables scalable production, monitoring, governance, and innovation for systematic strategies used by Trading and Structuring globally. You'll be based in our New York office.

Your expertise
• strong Python skills with experience delivering production-grade solutions
• hands-on experience with AI or machine learning in production or advanced prototyping
• experience with modern data platforms, cloud, or distributed systems
• strong data analysis and problem-solving skills in complex, fast-paced environments
• ability to work across technical and business domains with an end-to-end ownership mindset
• experience building monitoring, observability, or automation frameworks
• familiarity with systematic strategies, quantitative finance, or front office platforms
• proven track record of moving solutions from prototype to production or mentoring others
• You're curious to explore how AI can improve how we build, deliver, and optimize workflows. You do this with sound judgment - validating outputs and aligning with policies, risk standards, and ethical use.

*LI-UBS
*UBS-MOGUL

About UBS

UBS Group AG is a Swiss multinational investment bank and financial services company founded in 1862 and headquartered in Zurich, Switzerland. UBS is one of the largest and most respected financial institutions in the world, with a presence in over 50 countries. The company offers a wide range of financial services to its clients, including wealth management, investment banking, asset management, and retail banking. UBS is committed to providing its clients with innovative and effective financial solutions that meet their unique needs and goals.
Learn more about UBS
Size
71,697 employees
Market Cap
$64.8 billion
Industry
Founded
1854
5 Year Trend
-6.5%
NASDAQ

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