Finance AI/ML Engineer - PhD

Hewlett Packard Enterprise is seeking a Finance AI/ML Engineer - PhD to join their team in Spring, Texas.

As a Finance AI/ML Engineer - PhD, you will develop and program integrated software algorithms to structure, analyze, and leverage structured and unstructured data in business and systems applications. You will apply machine learning and statistical modeling to improve forecasting, data quality, and decision accuracy. Your primary focus will be on turning financial and operational data into AI-enabled insights and automation that help HPE plan, forecast, and operate more effectively.

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.
• Partner with data scientists, software engineers, product managers, and Finance domain experts to understand requirements and integrate AI solutions into existing systems and workflows.
• Keep clear documentation of methodologies, code, and results so models are auditable, explainable, and compliant with Finance controls.
• Present findings and recommendations to Finance stakeholders in plain language. Maintain dashboards and BI tools (e.g., Power BI) as needed.
• Participate in design reviews, stand-ups, and feedback cycles with your manager and team to ensure quality and continuous improvement.

Education and Experience Required:

• PHD in Mathematics, Applied Mathematics, Statistics, or a closely related quantitative field.

Knowledge and Skills:

• Proficiency in Python, R, or Java, plus SQL and databases. Familiarity with scikit-learn, TensorFlow, or PyTorch is highly beneficial.
• Solid understanding of statistics, probability, linear algebra, calculus, and optimization methods.
• Working knowledge of core ML concepts, including supervised and unsupervised learning, with exposure to deep learning, NLP, and time-series methods.
• Experience with large datasets, data cleaning, and exploratory analysis. Experience with visualization tools (Matplotlib, Tableau, or Power BI).
• Clear written and verbal communication, with the ability to explain complex concepts to non-technical audiences.

Nice to have:

• Exposure to GenAI/LLM tools.
• Familiarity with ERP/SAP data.
• Interest in finance and business strategy.

We offer a comprehensive suite of benefits that supports the physical, financial, and emotional wellbeing of our team members and their loved ones. We invest in your career and provide opportunities for growth and development.