# CO Strategic Initiatives AIML Expert at HP

HP is hiring a CO Strategic Initiatives AIML Expert. Level rates it Builds AI ●●●●; you can [apply on HP](https://jobsbylevel.com/go/c37f41f2-c183-4b25-a251-140a7cdf365f?utm_medium=ai-agent).

AI Level 4, AI centrality 98 out of 100. Tlaquepaque, Jalisco, Mexico.

## Details

- Company: [HP](https://jobsbylevel.com/companies/hp)
- AI level: AI Level 4 (score 98 out of 100)
- Location: Tlaquepaque, Jalisco, Mexico
- Posted: October 28, 2026
- Apply: https://jobsbylevel.com/go/c37f41f2-c183-4b25-a251-140a7cdf365f?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=co-strategic-initiatives-aiml-expert-at-hp-2114d7

## Prepare for this job

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## Description

CO Strategic Initiatives AIML Expert Description - HP's Applied AI team is looking for a Data Scientist to boost AI/ML adoption in Commercial Organization processes & activities. Our ideal candidate will shape HP’s future of how to solve concrete business problems with the use of data science, by joining a very dynamic, highly skilled and diverse global team who is pushing the innovation frontier in the way we use AI & automation solutions to solve our stakeholders’ challenges. Working with us you will combine your modelling skills, business thinking, experimentation and optimization methods to build viable solutions for HP’s Commercial Organization. The Applied AI team is responsible for coordinating all efforts implied to increase AI & Automation adoption across HP’s Commercial Organization, providing RPA/AI/ML solutions to business use cases. The key areas in scope for the team are: · Funnel management – coordinating the development of solutions from idea submission to moving to production, according to the necessary technology and architecture required (RPA/AI/ML) · Community – upskilling people into Citizen Developers/ Data scientists who can build solutions themselves for team & personal productivity and boosting volunteering and contribution for these upskilled individuals If you are customer centric experienced professional creating value for business groups by developing viable and sustainable solutions using AI/ML, then you are the perfect candidate. You will work closely with cross-functional teams to identify opportunities, match with both traditional ML methods (forecasting algorithms, recommender systems) and Generative AI and large language models. and deploy solutions in real-world applications. Your expertise in AI algorithms, deep learning architectures, and advanced ML techniques will be crucial in driving innovative AI initiatives within the organization. MAIN RESPONSIBILITIES: · Accelerate GenAI & ML Adoption: Drive the adoption of Generative AI and Machine Learning technologies within HP’s Commercial Organization by identifying high-value business challenges and developing scalable, impactful solutions that enhance productivity, decision-making, and innovation. · Use Case Validation & Reusability: Collaborate with the AI & Automation Product Owner to validate backlog priorities, assess technical feasibility, and determine whether existing ML or GenAI assets can be scaled or adapted for new use cases. · End-to-End Solution Delivery: Partner with cross-functional teams—including data scientists, ML/GenAI engineers, data/cloud experts, and RPA developers—to turn business problems into viable, sustainable solutions using ML algorithms or GenAI architectures (e.g., RAG, LLMs). · Stakeholder Engagement: Work directly with business stakeholders to understand their needs, translate them into solution requirements, and provide actionable recommendations that align with business strategy. Ensure results from ML models or GenAI systems are clearly tied to tangible business outcomes. · Model Development & Deployment: Design and build both predictive ML models and GenAI solutions—from data preprocessing and feature engineering to model development, fine-tuning, evaluation, and deployment—leveraging Azure, Databricks, and other enterprise platforms. · GenAI-Specific Capabilities: Architect and implement Retrieval-Augmented Generation (RAG) systems, fine-tune LLMs, and apply advanced prompt engineering techniques to build chat-based tools, search augmentation solutions, and virtual assistants that deliver real business value. · Performance Monitoring & Validation: Conduct rigorous model evaluation and performance monitoring for both ML and GenAI models to ensure reliability, fairness, and compliance. Continuously improve models based on feedback and production results. · Communication of Insights: Translate complex ML/GenAI outcomes into business-friendly insights and visualizations. Present recommendations clearly to

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