工作职责：
1. 协助开展工厂运营相关的数据分析与智能化解决方案实施，包括质量控制、能耗分析等，识别业务痛点；
2. 使用 SQL、Python 等工具进行数据提取、预处理与分析，并通过可视化工具（如 Spotfire、Power BI）将结果转化为管理层的可执行信息；
3. 研究并应用先进算法模型（如时间序列预测、异常检测），评估其业务价值并支持“智能数据”方案的试点实施；
4. 参与制造业 AI 应用研究，包括质量检测、流程优化和预测性维护；
5. 在导师指导下参与项目日常工作，支持测试数据流的收集、处理和分析；
6. 应用自然语言处理、机器学习等方法进行数据分类、根因分析与模型优化；
7. 协助开展 AI 解决方案的可行性研究、成本效益分析，并支持技术报告撰写。
职位要求：
1. 硕士及以上在读，数据科学、计算机科学、统计学、工业工程、自动化、机械工程或相关专业；
2. 熟练掌握至少一种数据分析语言（如 Python 或 R），熟悉常用数据科学库（Pandas、NumPy、Scikit-learn 等）；
3. 具备扎实的数据处理能力和 SQL 使用经验；
4. 理解基本的机器学习与 AI 概念（如监督/无监督学习、深度学习）；
5. 具备逻辑思维与问题分析能力，善于解决复杂问题；
6. 良好的团队协作与跨学科沟通能力，能够清晰表达想法；
7. 积极主动，愿意在真实工厂环境中动手应用算法和模型。
优先条件：
1. 有制造业、物联网、大数据平台相关实习或项目经验；
2. 熟悉数据可视化工具（如 Spotfire、Power BI）；
3. 了解时间序列分析或预测性维护相关概念。
职位亮点：
1. 接触真实制造业大数据与世界级智能工厂场景；
2. 获得行业专家一对一指导，加速个人成长；
3. 具有挑战性和支持性的实习环境；
4. 出色的实习表现将有机会获得正式转正机会。
ESSENTIAL DUTIES AND RESPONSIBILITIES:
1. Assist in factory operation data analysis and smart solution implementation, including quality control and energy consumption analysis, to identify business pain points.
2 Use SQL, Python, and other tools for data extraction, cleaning, and analysis, and translate results into actionable insights via visualization tools such as Spotfire or Power BI.
3. Research and apply advanced algorithmic models (e.g., time-series forecasting, anomaly detection), evaluate their business value, and support pilot implementation of “smart data” solutions.
4. Participate in AI application research for manufacturing, including quality inspection, process optimization, and predictive maintenance.
5. Under mentor guidance, support daily project work, including collection, analysis, and processing of operational data.
6. Apply NLP and machine learning methods for data classification, root cause analysis, and model optimization.
7. Assist in feasibility studies, cost-benefit analysis, and preparation of technical reports for AI solutions.
QUALIFICATIONS REQUIRED:
1. Current master’s student or above in Data Science, Computer Science, Statistics, Industrial Engineering, Automation, Mechanical Engineering, or related fields.
2. Proficiency in at least one data analysis language (Python or R) and familiarity with common data science libraries (e.g., Pandas, NumPy, Scikit-learn).
3. Solid skills in data processing and SQL.
4. Understanding of fundamental machine learning and AI concepts (e.g., supervised/unsupervised learning, deep learning).
5. Strong logical thinking and problem-solving skills to tackle complex issues.
6. Good teamwork and cross-disciplinary communication skills with the ability to articulate ideas clearly.
7. Proactive mindset with willingness to apply code and models in real industrial settings.
PREFERRED QUALIFICATIONS:
1. Internship or project experience in manufacturing, IoT, or industrial data analysis.
2. Familiarity with data visualization tools such as Spotfire or Power BI.
3. Knowledge of time-series analysis or predictive maintenance concepts.
WHY JOIN US：
1. Hands-on exposure to real-world big data and world-class manufacturing environments.
2. One-on-one mentorship from experienced industry professionals.
3. A challenging yet supportive internship setting.
4. Outstanding interns may be considered for full-time opportunities after graduation.