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Are you ready to shape the future of the printing industry with the power of AI & ML? HP Industrial Print, a division of HP Inc., is at the forefront of providing innovative printing solutions and services for the graphic arts and commercial printing sectors. Our groundbreaking products and services enable businesses to stay ahead of market changes and expand their capabilities with world-class digital printing solutions with more than 8000 presses worldwide, serving 5500 customers across 82 countries, making HP a leader in the sector.
As part of the new division of Software & Solutions, our aim is to come together with AI & ML solutions and tools that help to automate and enhance the IoT ecosystem, and that's where you can play a huge role as a Senior Data Scientist. We're looking for a dedicated and talented Senior Data Scientist who is excited about solving complex problems and deriving insights from data to drive impactful business decisions. Your expertise in data science, statistical analysis, and machine learning will be crucial in advancing our data-driven projects.
Key Responsibilities:
Develop and implement machine learning (ML) models and other algorithms to solve business problems.
Design and conduct experiments, tests, and analyses to develop machine learning models, including both traditional ML and LLMs, for integration into our software portfolio, enhancing product capabilities with AI-driven features.
Leverage large language models (LLMs) to extract insights, perform natural language processing (NLP) tasks, and automate text generation for business applications.
Collaborate with architects, data engineers, software engineers, and product managers to integrate AI solutions into products and services.
Perform data wrangling, cleaning, and preprocessing to ensure high-quality data for ML models.
Build and maintain predictive models, optimizing their performance for accuracy, scalability, and interpretability.
Monitor and validate model performance, fine-tuning and retraining as necessary to improve results.
Stay updated with the latest developments in AI and machine learning technologies and incorporate them into ongoing projects.
Present findings and recommendations to both technical and non-technical stakeholders through clear and concise reports and visualizations.
Ensure compliance with data privacy regulations and ethical guidelines in the handling of data and development of data-driven models.
