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
Monitor and explain P&L, performance and risk for Quantitative Strategies Portfolio Managers across global futures, FX, rates, equity index and commodities, engaging with them on a regular basis. Build quantitative models and analytics for performance attribution and risk analysis, working with large and diverse datasets.
Locations (2)
New York, New York, United States
London, England, United Kingdom
Compensation
The estimated base salary range for this position is $160,000 to $250,000, which is specific to New York and may change in the future.
Responsibilities
Monitor and explain P&L, performance and risk for Quantitative Strategies Portfolio Managers across global futures, FX, rates, equity index and commodities
Build quantitative models and analytics for performance attribution and risk analysis
Research and implement new risk methodologies and techniques to represent and monitor systematic strategies
Develop and refine simulation models for risk measurement, such as VaR enhancements, scenario analysis and factor modeling
Design and enhance pricing models and visualization tools that make risk and performance transparent to Portfolio Managers and the broader Risk team
Help turn the next generation of geospatial intelligence ideas into real-world capabilities by building and refining Python-based applications and cloud-enabled workflows in AWS.
Compensation
$125,000–$155,000
Responsibilities
Develop, sustain, debug, and test Python software components, including concurrent and multi-process applications.
Build and support event-driven systems, queues, producer/consumer pipelines, and distributed or microservices architectures.
Develop and integrate solutions using AWS services and cloud-based processing workflows.
Conduct design and code reviews and collaborate across technical teams.
Implement and test statistical, optimization, similarity-scoring, probabilistic-matching, and assignment methods in code.
Finance AI/ML Engineer - PhDNewHPE · Spring, US
Quant Risk ResearcherNewMillennium · New York, US+1 more
Senior Operations Research DeveloperSouthwest Airlines · Remote, US