數據科學家(統計) Data Scientist(Statistician) (Data Science & AI Team)

＜About the Job＞ 

As an Optimization Data Scientist, you will play a key role in driving Optimization and Operations Research initiatives across critical business functions, including supply chain, production planning and scheduling, capacity allocation, inventory and logistics, industrial engineering, and financial performance. Leveraging advanced mathematical modeling and algorithm design, you will transform complex data into actionable insights, enabling smarter decisions and unlocking optimization-driven business value. 

＜Job Responsibilities＞ 

．Design, implement and refine advanced Mathematical Programming / Operations Research / Meta-heuristics / Numerical Simulation / Optimization Algorithm Models (at least one of the fields).  

．Ensure alignment of optimization initiatives with the requirement goal defined by key stakeholders and company objectives and identify new formulations or decomposition strategies for model improvements.  

．Executing large-scale optimization projects, including problem formulation, constraint engineering, model building, algorithm development, solver tuning, and deployment, etc.  

．Works closely with a team of project manager, data scientist, business data analyst, data engineer, supply chain / IE / PMC domain expert, etc.  

．Collaborate effectively with team members, whether leading tasks or supporting initiatives led by others.  

．Self-motivated, Result-oriented, and interested in applying quantitative & optimization methods to solving real-world supply chain, manufacturing, and engineering problems. 

＜Skills＞ 

．Experience with any one of Mixed Integer Programming (MILP), Linear Programming (LP), Non-linear Programming (NLP), Constraint Programming (CP), Meta-heuristics (GA / SA / Tabu Search / ALNS…), Stochastic / Robust Optimization, Numerical Simulation…, etc., model/algorithm building of the practical application in the industry.  

．Hands-on experience with commercial or open-source solvers such as Gurobi, Cplex, OR-Tools, or SCIP.  

．Familiarity with programming languages like Python or C++ or Java.  

．Advanced ability to perform problem decomposition, constraint analysis, and working knowledge of operations research theory.  

．Ability to visualize optimization results, KPI trade-offs, and solver behavior (e.g., gap convergence, IIS diagnostics) in the most effective way possible for a given task, especially debug and troubleshoot infeasible / unbounded models.  

＜Minimum Qualifications＞： 

．2+ years of professional experience with a degree of Ph.D. / Ph.D. Candidate, or 3+ years of relevant working experience with a degree of Master. 

．Major in Industrial Engineering / Operations Research / Computer Science / Information Engineering / Information Management / Applied Mathematics / Supply Chain Management or related quantitative discipline (such as in a field where there is intensive training in quantitative & optimization methods, e.g., Operations Research, Industrial Engineering, Management Science, Transportation, Logistics, Statistics, Economics, Electrical and Computer Engineering, Physics).

協助全球 AI 算力平台架構的環境佈署與配置作業；參與雲端服務資源的日常維運、自動化資源分配之參數設定及性能監控。配合利用容器化技術 (Docker/K8s) 進行效能瓶頸初步排查，支援優化 MLOps 工作流並協助撰寫技術維護文件。 

Assist in environmental deployment and configuration of global AI computing platforms. Participate in daily operations of cloud resources and parameter setting for automated resource allocation. Support initial performance troubleshooting using container technologies (Docker/K8s) and help optimize MLOps workflows and documentation.

參與電腦視覺與 NLP 技術研發，協助開發領域專屬模型。配合設計 AI 應用框架，支援將生成式 AI 導入實際製造場景；協助執行數據標註與推理效能評估。 

Participate in CV and NLP R&D; Assist in domain-specific model development. Support AI application frameworks and GenAI implementation in manufacturing; Assist in data labeling and inference evaluation.

＜About the job＞： 

The Data Science & AI team of headquarter IT is developing the frontier and practical analytic technologies that enhance the data value. As the data scientist, you‘ll join the AI/Big Data Analytics program/projects related to management topics, including Commercial/Industrial Engineering/Supply Chain/Financial Performance/Operation...etc., to build the model or algorithm to empower data-driven & analytics-driven for driving business value from data insights in this world-class company (Fortune Global 500, 22nd). 

＜Job Description＞：  

．Design, implement and refine advanced Statistical Modeling/Machine Learning/Deep Learning/Numerical Simulation/Optimization Algorithm Models(at least one of the fields) 

．Ensure alignment of modeling initiatives with the requirement goal defined by key stakeholders and company objectives and identify new hypotheses for model improvements.  

．Executing big data analysis and predictive analytics projects include feature engineering, model building, algorithm development, etc.  

．Works closely with a team of data system analysts, business data analysts, data engineers, data platform architects, etc.  

．Collaborate effectively with team members, whether leading tasks or supporting initiatives led by others. 

．Self-motivated, Result-oriented, and interested in applying quantitative methods to solving business and engineering problems. 

＜Skills＞ 

．Experience with any one of Machine Learning, Statistical Modeling, Deep Learning(Nature Language/Image), Econometric Modeling, Optimization Algorithm(OR), Numerical Simulation..., etc., model/algorithm building of the practical application in the industry. 

．Familiarity with programming languages like Python or R, or Java. (Good programming skills in Python is a plus).  

．Advanced ability to perform Exploratory Data Analysis and working knowledge of statistics.  

．Ability to visualize data in the most effective way possible for a given task, especially visualize models and results and debug and troubleshoot code and models. 

．Big on finding the many insights based on the data and being passionate and patient about working with complex data.

工作內容： 

＜About the job＞： 

We‘re seeking AI/ML enthusiasts with experience and skills in working and are passionate about extending AI/ML expertise. The Data Science & AI team of headquarter IT is developing the frontier and practical analytic technologies that enhance the data value. As the AI/ML engineer, you‘ll join the AI/Big Data Analytics program/projects of headquarter IT and assist in building the model/algorithm to empower data-driven & analytics-driven for driving business value from data insights in this world-class company (Fortune Global 500, 22nd). 

＜Job Type Option：＞  

*Type1: AI/ML Engineer (Engineering-Oriented)  

(1) Use Machine Learning/Deeping Learning/Analytical techniques to build models for internal different scenarios and requirements.  

(2) Building the model lifecycle from data exploration to feature engineering to model evaluation and validity analysis capabilities.  

(3) Execute efficient, scalable, automated processes for model development, model validation, and model implementation  

(4) Deploy the model to production and maintain/optimize the models by MLOps. 

(5) Experience in Azure Data Lake, Azure Databricks, and Azure Data Factory is preferred. 

(6) Experience in AWS SageMaker is preferred. 

*Type2: NLP AI Engineer 

(1) Focused on NLP Algorithm/Machine Learning & Deeping Learning for Text. 

(2) Develop the Algorithm of NLP(Natural Language Processing)/ Computational Linguistics/Text Mining/Topic Modeling 

(3) Join the project to build the end-to-end NLP systems, from understanding the requirements to selecting training datasets to model, evaluate, and deliver/deploy NLP models. 

(4) Fine-tune LLMs and optimize and resolve issues related to LLM usage in production scenarios, enhancing reliability, accuracy, and performance. 

*Type3: AI/ML Engineer (Analytics-Oriented) 

(1)Use Machine Learning/Deeping Learning/Analytical techniques to build models for internal different scenarios and requirements. 

(2)Build the model lifecycle, e.g., from data exploration to feature engineering to model evaluation and validity analysis capabilities. 

(3)Execute efficient, scalable, automated processes for model development, model validation, and model implementation. 

(4)Apply quantitative methods including but not limited to above tasks to solve business problems. 

(5)Being passionate and patient about working with complex data 

＜Skills＞ 

．Type1 & 3 : AI/ML Engineer(Engineering-Oriented & Analytics-Oriented)  

(1)Familiarity with any one of Machine Learning, Statistical Modeling, Deep Learning (Nature Language/Image/Time Series) model/algorithm building of the practical application in the industry. 

(2) Being familiar with Python Libraries, e.g., Numpy, Pandas, Scikit-Learn, SciPy, Matplotlib, etc.  

(3)(For Engineering-Oriented) Knowledge of Big Data with Machine Learning/Statistical modeling related technologies such as Spark MLlib or PySpark or SparkR/SparklyR.  

(4)(For Analytics-Oriented) Knowledge of Deep Learning Framework such as TensorFlow/Caffe/Pytorch/Keras. 

．Type 2: NLP AI Engineer 

(1) Experience with text mining algorithms such as word segmentation, POS tagging, named entity recognition...etc.  

(2) Experience in algorithms and libraries of NLP(Natural Language Processing), especially in machine learning techniques applied to NLP, such as Text mining, Text classification, Information Extraction, Keyword Tagging, and content discovery. 

(3) Familiar with one general-purpose programming language (e.g., Python, Java, C/C++) 

(4) Experience manipulating and integrating unstructured, semi-structured, and structured data. 

(5) Excellent knowledge and demonstrable experience using open-source NLP packages such as NLTK, Word2Vec, Standford CoreNLP, SpaCy, and Gensim. 

(6) Knowledge of Open source LLMs, such as BERT, BLoom, LLaMA..., etc., and NLP frameworks, like Hugging Face Transformers, PyTorch /JAX

1.車用ADAS 攝影鏡頭、光達、雷達相關應用 

2.建立感知融合策略經驗(Camera Radar/Camera 

3.點雲物件辨識模型建立 

4.串接自動駕駛模擬器與系統驗證開放式平台之軟硬整合 

5.配合開發流程撰寫相關文件 

6.熟悉以下語言/ 一項或多項))：C++/Python/TensorFlow/PyTorch 程式開發能力，具ROS2 相關開發經驗尤佳 

7.主管交辦事項

1.數據治理實施，包括資料模型、資料定義、元數據、資料品質等 

2.建構數據工作流(Data Pipeline)、導入數據工程自動化和敏捷實踐(DataOps) 

3.熟悉數據架構規劃、數據源開發、數據蒐集與處理、數據探勘與加值 

4.數據建模 : 依主題挑選適當模型方法與參數處理進行多類型建模與冠軍模型挑選，與商業分析師合作進行統計分析模型及最佳化的研究與開發。 

5.視覺化應用 : 善用視覺化工具(PowerBI)溝通特徵值與模型分析結果。 

6.具備跨單位的大型專案管理實務 

7.具備良善的溝通技巧及專案團隊協作能力

＜About the job＞  

As the Senior Data Engineer or Data Architect, you‘ll join the various advanced Data Science & AI Projects in the corporate headquarters. As well as developing intelligent applications via related AI and Big Data Analytics Technology for digital transformation, you will have plenty of opportunities to develop emerging applications based on different use cases and expand your tech skillset in this world-class company (Fortune Global 500, 20th). 

＜Job Description＞ 

*Type 1：Senior Data Engineer 

Responsible for acquiring data using API, Web scraping, or other data accessing protocol/scripting and developing the ETL data pipelines, and the data aggregation systems. Using software development experience to design and build high-performance automated systems. As below: 

1. Data Processing 

(1)Data ETL(Extracting/Transforming/Loading) process engineering and querying from relational data management(such as SQL Script). 

(2)Building systematic data quality processes and checks to ensure data quality and accuracy. 

(3)Solid coding experience in Python or Java. 

2. Data Pipeline Development 

(1)Develops a data integration process, including creating scalable data pipelines and building out data services/data APIs. 

(2)Create a data processing automation and monitoring mechanism by optimizing the data pipeline process.  

(3)Experience with dataflow/workflow/management tools, such as Apache Nifi, Apache Airflow, Azkaban, etc., is preferred. 

3. Data Crawling 

(1)Build scalable tools that automate web crawling, scraping, and data aggregation from various web pages using frameworks such as Scrapy. 

(2)Accessing data from REST APIs, particularly in parsing data in disparate formats such as JSON and XML, and developing automated engineering.  

(3) (Nice to Have) Knowledge of server-based front-end/UI technologies, including Vue/React and HTML/CSS, is preferred. 

*Type 2：Data Architect 

Responsible for designing, implementing, and maintaining scalable and reusable system architectures/data architectures for complex data structures and large data in data science and AI projects. As below: 

1. Data Schema Design 

(1)Collaborate with the team to design DB/Table Schema and Data Schema. 

(2)Consolidate the requirements and use data engineering tech to design and implement a robust Data Mart.  

(3)Experience handling all kinds of structured/semi-structured/unstructured data and streaming data is preferred. 

(4)Hands-on experience with Dimensional Data Modeling(Column-based data warehouse) or NoSQL Schema design. 

2. Data Platform Architecture 

(1)Design and build data infrastructure/platform components to support complex data pipelines ingesting various data from multiple internal and external data sources and processing. 

(2)Familiar with Big Data frameworks and processing technologies, ex: Hadoop, Apache Spark, NoSQL ...etc. 

(3)Familiar with AZURE or AWS cloud data services(hands-on experience with cloud infrastructure will be a plus) 

(4)Familiarity with the Linux OS environment, the Shell Scripting, and infrastructure knowledge.  

(5)(Nice to Have)Experience with declarative infrastructure/container technologies, such as Docker and Kubernetes (k8s/k3s). (Nice to Have).