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About Company
Lenovo is a US$69 billion revenue global technology powerhouse, ranked #196 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world’s largest PC company with a full-stack portfolio of AI-enabled, AI-ready, and AI-optimized devices (PCs, workstations, smartphones, tablets), infrastructure (server, storage, edge, high performance computing and software defined infrastructure), software, solutions, and services. Lenovo’s continued investment in world-changing innovation is building a more equitable, trustworthy, and smarter future for everyone, everywhere. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY).
Job Overview
This Data Scientist role at Lenovo involves using data and AI to solve business problems.
- Build and use machine learning models
- Analyze large amounts of data to find useful insights
- Work with different teams to turn data into real solutions
- Improve and optimize AI systems
- Keep learning new AI technologies
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Skills Needed
🔹 Technical Skills
- Basics of machine learning and AI
- Understanding of data analysis and modeling
🔹 Programming
- Good knowledge of Python
- Familiarity with tools like TensorFlow or PyTorch
- Basic idea of working with large datasets
🔹 Other Skills
- Problem-solving ability
- Logical thinking
- Good communication skills
Qualifications
- Degree in Computer Science, Data Science, Math, Statistics, or similar field
- Some experience (projects or job) in data science or machine learning
- Knowing how to build simple models or work with data is a plus
Roles & Responsibilities
- Collect, process, and analyze large datasets from various sources to support business objectives and product development.
- Develop and deploy machine learning models and algorithms to solve complex business problems and improve customer experiences.
- Perform data exploration and visualization to uncover trends, patterns, and insights.
- Collaborate with cross-functional teams, including sales, marketing and product managers/engineers, and business analysts, to integrate data-driven solutions.
- Communicate findings and insights to stakeholders through clear and compelling data visualizations and reports.
- Stay current with the latest advancements in data science, machine learning, AI and industry trends to continuously enhance our data and analytics capabilities.
- Research and apply multidisciplinary techniques, findings and approaches to solutions driving the business’ understanding of its market, its internal operations, and its opportunities
- Review, implement and analyze algorithms that will substantially improve analytics capability of the business
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