Develops and programs integrated software algorithms to structure, analyze, and leverage structured and unstructured data in business and systems applications.
Compensation
The expected salary/wage range for this position is provided below. Actual offer may vary from this range based upon geographic location, work experience, education/training, and/or skill level. – United States of America: Annual Salary USD 95,800 - 220,500 in Texas
Responsibilities
Design, develop, and implement AI and machine learning models, including data pre-processing, feature engineering, algorithm selection, training, and evaluation.
Build forecasting and predictive models for revenue, cost, and demand, and support scenario and "what-if" analysis for planning.
Gather, clean, and analyze large financial and operational datasets to train and test models, using statistical methods and visualization to surface insights.
Optimize models for performance through hyperparameter tuning, experimentation, and feature selection or dimensionality reduction.
Support GenAI and automation use cases (AI assistants, agents, workflow automation) across FP&A, cost accounting, and controllership.
Requirements
PhD in Mathematics, Applied Mathematics, Statistics, or a closely related quantitative field
Nice to have: GenAI/LLM tools
Nice to have: ERP/SAP data
Nice to have: interest in finance and business strategy
Lead AI and data science initiatives across the Investment Bank, designing, building, and deploying production-grade AI solutions.
Locations (2)
Zurich, Zurich, Switzerland
London, England, United Kingdom
Responsibilities
Partner with stakeholders to identify high-value opportunities and deliver measurable business outcomes such as revenue enablement, risk reduction and productivity
Design, build and deploy production-grade AI solutions across the Investment Bank
Create reusable products using LLMs, agentic systems, machine learning and rules-based analytics
Drive delivery from discovery and prototyping through integration, deployment and adoption
Develop reusable patterns for APIs, system integration, orchestration and observability
Requirements
Master’s degree or PhD in Computer Science, Engineering, Mathematics, Physics, Quantitative Finance or a related field, or equivalent practical experience
Partner with stakeholders to identify high-value opportunities and deliver measurable business outcomes such as revenue enablement, risk reduction and productivity by designing, building, and deploying production-grade AI solutions across the Investment Bank.
Locations (2)
London, England, United Kingdom
Zurich, Zurich, Switzerland
Responsibilities
Partner with stakeholders to identify high-value opportunities and deliver measurable business outcomes such as revenue enablement, risk reduction and productivity
Design, build and deploy production-grade AI solutions across the Investment Bank
Create reusable products using LLMs, agentic systems, machine learning and rules-based analytics
Drive delivery from discovery and prototyping through integration, deployment and adoption
Develop reusable patterns for APIs, system integration, orchestration and observability
Requirements
Master’s degree or PhD in Computer Science, Engineering, Mathematics, Physics, Quantitative Finance or a related field
