Jobs in the United States

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Data Engineer
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- $95,000 to $120,000 USD / year
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Hewlett Packard Enterprise

Finance AI/ML Engineer - PhD

Spring, TX, United States

$95,800 to $220,500 USD / year

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Job details

Pay: $95,800 to $220,500 USD / year
Posting language: English
Posted: Nov 12, 2026

Original job description

Finance AI/ML Engineer - PhD

This role has been designed as ‘’Onsite’ with an expectation that you will primarily work from an HPE office.

Who We Are:

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.

Job Description:

Develops and programs integrated software algorithms to structure, analyze, and leverage structured and unstructured data in business and systems applications. Applies machine learning and statistical modeling to improve forecasting, data quality, and decision accuracy. Formulates descriptive, diagnostic, predictive, and prescriptive insights and translates business requirements into code. In Finance, this means turning financial and operational data into AI-enabled insights and automation that help HPE plan, forecast, and operate more effectively.

Finance is shifting from reporting to decision intelligence. You'll apply a strong quantitative foundation to real finance problems, including forecasting, scenario planning, automation, and GenAI-enabled insights. You'll work alongside Finance leaders, data scientists, and AI/ML engineers. We hire for mathematical rigor, curiosity, and the ability to learn fast. Finance expertise is something you'll build here.

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.

Accessibility

HPE is committed to creating an inclusive and accessible workplace and encourages applications from all qualified individuals, including those with disabilities. If you believe you require accommodation during any stage of the application or interview process, please submit your request by completing our secure form linked here.

Note: This option is reserved for applicants needing assistance/reasonable accommodation related to a disability.

What We Can Offer You:

Health & Wellbeing We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.

Personal & Professional Development We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have - whether you want to become a knowledge expert in your field or apply your skills to another division.

Unconditional Inclusion We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.

Let's Stay Connected:

Follow @HPECareers on Instagram to see the latest on people, culture and tech at HPE.

Job:

EngineeringJob Level:

TCP_02 "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 The listed salary range reflects base salary. Variable incentives may also be offered."

Information about employee benefits offered in the US can be found at https://myhperewards.com/main/new-hire-enrollment.html

HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity.

Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.

HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.

Recruitment Fraud Alert

We have become aware of an increase in fraudulent recruitment activities in which individuals impersonate our company or authorized recruitment agencies to offer fake employment opportunities. These scams may occur through false websites, emails, social media, or chat-based applications and often aim to obtain personal information or money. Please note that Hewlett Packard Enterprise (HPE), its direct and indirect subsidiaries and affiliated companies, and its authorized recruitment agencies/vendors will never charge a candidate a registration fee, hiring fee, or any other fee in connection with its recruitment and hiring process. We also never request personal information such as back account details, Social Security numbers, or national IDs via social media or chat applications.

All legitimate job opportunities will come through official company channels, and candidates are responsible for verifying the credentials of any third party claiming to represent the company. Any reliance on fraudulent communication is at the individual’s own risk, and HPE disclaims legal liability for any resulting damages. If you suspect recruitment fraud, do not share personal information or make any payments and report the incident to your local authorities immediately.

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Jobs in the United States