Revenue AI Solutions Analyst

Job Description

We are seeking a hands‑on AI builder to join Revenue Operations and help turn high‑impact business use cases into real, deployed AI solutions. This is not a research or strategy‑only role. You will design, build, and operationalize AI capabilities that are embedded directly into how Sales, Operations, and Finance work every day.

As a Revenue AI Solutions Analyst, you will work at the intersection of business, data, and enterprise systems. You will partner closely with Sales Operations, Customer Operations, Service Operations, Finance, IT, and Data teams to translate real operational problems into working AI solutions and bring them into production.

• Design and build AI and machine learning solutions across forecasting, pricing, Sales 360, service operations, and RMA.
• Translate business workflows and use cases into scalable AI architectures and implementations.
• Build prototypes, MVPs, and production‑ready solutions using predictive models, ML pipelines, and LLM‑based agents.
• Embed AI capabilities into Salesforce and the broader Revenue Operations technology stack.
• Work hands‑on with domain teams to iteratively refine use cases and solutions based on real‑world constraints.
• Partner with IT, Data, and Security teams to ensure solutions are scalable, secure, and compliant.
• Help define standards, patterns, and best practices for AI adoption within Revenue Operations.

• Not a research or academic AI role
• Not a strategy‑only or slide‑focused role
• Not a vendor management or consulting coordination role
• Not a traditional data scientist working in isolation

This role will have direct impact on revenue predictability, margin protection, and operational scale. You will help accelerate San Disk’s adoption of AI in ways that materially change how the company operates, making Revenue Operations smarter, faster, and more resilient.

• Minimum 5‑7 years experience
• Bachelor’s degree required, Master’s degree preferred.
• Strong hands‑on experience with Python and modern AI/ML frameworks.
• Experience building predictive models, ML pipelines, or LLM‑based solutions.
• Experience integrating AI into enterprise systems such as CRM, ERP, or data platforms.

• Ability to work with imperfect, real‑world business data
• Strong understanding of business processes in Sales, Operations, or Revenue environments
• Ability to explain technical concepts clearly to non‑technical stakeholders
• Pragmatic, delivery‑oriented mindset with a bias for action

Sandisk is committed to providing equal opportunities to all applicants and employees and will not discriminate against any applicant or employee based on their race, color, ancestry, religion (including religious dress and grooming standards), sex (including pregnancy, childbirth or related medical conditions, breastfeeding or related medical conditions), gender (including a person’s gender identity, gender expression, and gender‑related appearance and behavior, whether or not stereotypically associated with the person’s assigned sex at birth), age, national origin, sexual orientation, medical condition, marital status (including domestic partnership status), physical disability, mental disability, medical condition, genetic information, protected medical and family care leave, Civil Air Patrol status, military and veteran status, or other legally protected characteristics.

We also prohibit harassment of any individual on any of the characteristics listed above. Our non‑discrimination policy applies to all aspects of employment. We comply with the laws and regulations set forth in the Know Your Rights:
Workplace Discrimination is Illegal poster. Our pay transparency policy is available here.

Sandisk thrives on the power and potential of diversity. As a global company, we believe the most effective way to embrace the diversity of our customers and communities is to mirror it from within. We believe the fusion of various perspectives results in the best outcomes for our employees, our company, our customers, and the world around us. We are…