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Automation-Data Engineering / Analytics

Lenovo -
São Paulo, SP

Candidate-se Agora

Detalhes da vaga

Tempo integral
Há 1 dia

Qualificações

Estatística
Azure
Gestão
Ciência da Computação
Certificação AWS
Mestrado
Machine Learning
ETL
Data science
Inteligência artificial
Habilidade de Comunicação
Python
Analíticos

Descrição completa da vaga

General Information

Req #

WD00100408

Career area:

Information Technology

Country/Region:

Brazil

State:

São Paulo

City:

Sao Paulo

Date:

Monday, June 8, 2026

Working time:

Full-time

Additional Locations:

Brazil - São Paulo - São Paulo

Brazil - São Paulo - Sao Paulo

Why Work at Lenovo

We are Lenovo. We do what we say. We own what we do. We WOW our customers.

Lenovo is a US$83 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).

This transformation together with Lenovo’s world-changing innovation is building a more inclusive, trustworthy, and smarter future for everyone, everywhere. To find out more visit www.lenovo.com, and read about the latest news via our StoryHub.

Description and Requirements

Role Overview

This role focuses on driving data-driven transformation across IT operations by leveraging advanced analytics, machine learning, and Generative AI.

You will play a key role in improving service quality, enhancing the digital employee experience (DEX), and enabling smarter decision-making through data and AI-driven insights.

Key Responsibilities

Apply data analytics, predictive modeling, and observability to support continuous improvement across IT operations
Transform operational data into actionable insights and recommendations to drive decision-making
Enhance Digital Employee Experience (DEX) through proactive, AI-driven issue identification and service improvements
Develop and implement Generative AI solutions (e.g., conversational AI, knowledge automation) to optimize user journeys
Design, build, and maintain machine learning models to identify patterns, trends, and root causes in IT data
Build and manage data pipelines and data models to support analytics, reporting, and AI initiatives

Key Skills & Competencies

Strong written and verbal communication skills
Proficiency in Python and experience with data science and AI/ML frameworks
Knowledge of data engineering concepts (ETL, data pipelines, data lakes, cloud ecosystems such as AWS or Azure)
Experience with observability and analytics tools for monitoring and optimization
Ability to translate business problems into analytical models and AI-driven solutions
Strong problem-solving skills with the ability to apply advanced technical concepts across domains

Qualifications & Experience

Experience:
Proven experience in Data Science, Machine Learning, or AI Engineering roles
Experience deploying AI/ML models in production environments, ideally within IT operations or service management
Hands-on experience with Generative AI and conversational platforms
Education:
Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field
Preferred Certifications & Knowledge:
Certifications in AI/ML, Data Science, or Cloud platforms
Strong foundation in statistics, data modeling, and AI concepts
Continuous learning mindset, particularly in emerging areas such as Generative AI and advanced analytics

Additional Locations:

Brazil - São Paulo - São Paulo

Brazil - São Paulo - Sao Paulo

Brazil

Brazil - São Paulo

* Brazil - São Paulo - São Paulo , * Brazil - São Paulo - Sao Paulo

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