基本信息

职位编号:
100016076
工作领域:
Data Management and Analytics
国家/地区:
中国
省:
天津
市:
天津(Tianjin)
日期:
星期二, 6 月 17, 2025
其他工作城市
* China - Beijing - Beijing
* China - Guangdong - Shenzhen
* China - Tianjin - Tianjin

为什么选择联想

联想文化,我们称之为 “We Are Lenovo”(我们,就是联想),其核心是:“说到做到,尽心尽力,成就客户”。

联想集团是一家年收入569亿美元的全球化科技巨头,位列《财富》世界500强第248名,服务遍布全球180个市场数以百万计的客户。为实现“智能,为每一个可能” 的公司愿景,联想在不断夯实全球个人电脑市场冠军地位的基础上,积极构建全栈式的计算能力,现已拥有包括人工智能赋能、人工智能导向和人工智能优化的终端、基础设施、软件、解决方案和服务在内的完整产品路线图,包括个人电脑、工作站、智能手机、平板电脑等终端产品,服务器、存储、边缘计算、高性能计算以及软件定义等基础设施产品。这一变革与联想改变世界的创新一起,共同为世界各地的人们成就一个更加包容、值得信赖的智慧未来。联想集团有限公司在香港交易所上市(港交所:992)(美国预托证券代号:LNVGY)。

欢迎访问联想官方网站 https://www.lenovo.com,并关注“联想集团”微博及微信公众号等社交媒体官方账号,或关注“联想招聘”公众号,获取联想最新动态。

职位描述和要求:

Job Responsibilities:

1. Understand analysis requirements and evaluate viability from data analysis point of view.

2. Understand the data structure and suggest with later analysis requirements.

3. Perform exploratory data analysis (EDA) to uncover initial insights and patterns.

4. Identify trends, correlations, and insights that answer the business questions.

5. Validate findings with statistical significance and reliability.

6. Implement machine learning models or statistical methods to analyze data and extract meaningful patterns.

7. Optimize algorithms to enhance the efficiency and accuracy of analysis.

8. Interpret the analysis results, connecting them back to the original business problem.

9. Review visualizations to ensure they meet business needs and are easily interpretable by the target audience. Suggest modifications or additional visuals based on stakeholder feedback.

10. Ensure all data analysis steps are well-documented. Identify any gaps, errors, or areas for improvement in the analysis process. Prepare and present the final analysis report to stakeholders, incorporating their feedback as needed.


Job Requirements:

1. Ability to understand business problems and translate them into analytical objectives.

2. Proficient in performing exploratory data analysis (EDA) to uncover trends, distributions, anomalies, and correlations.

3. Skilled in using tools like Python (Pandas, Seaborn), R, or SQL to perform data slicing and summarization.

4. Comfortable with statistical validation methods (e.g., hypothesis testing, confidence intervals) to confirm robustness of findings.

5. Experience implementing machine learning models, statistical models, or optimization algorithms to generate predictive or prescriptive insights.

6. Ability to evaluate model performance and tune parameters for improved accuracy and relevance.

7. Understand when and how to use supervised/unsupervised models or statistical testing techniques.

8. Able to interpret analysis results and explain them in the context of the original business problem.

9. Bridge the gap between technical analysis and business understanding, offering practical and actionable recommendations.

10. Proficient in visualization tools such as Power BI, or programming Python libraries like Plotly, ggplot2, or Matplotlib.

11. Capable of tailoring visuals to different audiences and modifying visualizations based on stakeholder feedback.

12. Identify and flag any analytical risks, data quality issues, or gaps during the process.

13. Open to Several Locations: Tianjin, Beijing, Shenzhen

其他工作城市
* China - Beijing - Beijing
* China - Guangdong - Shenzhen
* China - Tianjin - Tianjin
* China - Beijing - Beijing , * China - Guangdong - Shenzhen , * China - Tianjin - Tianjin
* China - Beijing , * China - Guangdong , * China - Tianjin
* China