面議(經常性薪資達4萬元或以上) 新北市土城區 5年工作經驗 6天前更新
<About the job>
As the AI System Analyst, 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>
Responsible for gathering and analyzing the requirements and contributing to designing, developing, testing, and deploying in all phases of the AI system development project lifecycle, as below:
1. Collaborate with business data analysts to analyze user requirements and ensure that requirements and acceptance criteria satisfy user needs.
2. Create a system requirement specification to elaborate on system design, system components/interfaces, and data schema.
3. Work with the multi-functional engineering team(e.g., data scientist, AI/ML engineer, data engineer, AI software engineer..., etc.) to ensure technical feasibility.
4. Drive usability and quality of the AI system developed and ensure all system requirements are well implemented.
5. Work on various enterprise AI system applications and problems, and analyze issues to identify root causes and prevention.
6. Create the Wireframes(or UI Prototypes) for AI system feature discussion with users and provide them to the UI/UX design team.
7. Author and update internal documentation; initiate and deliver requirement specification and system analysis/system design documentation.
<Required Skills>
1. Practical experience in requirements gathering and analysis and change management
2. Experience co-working with front-end and back-end system development teams.
3. Strong analytical, verbal, and written communication, teamwork, and highly collaborative skills.
4. Experience with Microsoft Visio, Axure RP(or other wireframe tools).
5. Practical experience in Relational DB (e.g., MS SQL, PostgreSQL) and ability to write SQL queries.
6. Mastery of Microsoft Office programs (Word, Excel, PowerPoint)
(Nice to have, but not necessary)
1. Mastery of QA methodology and problem-solving tools/techniques in software engineering.
2. Knowledge of AI/Data Science Tech(e.g., Machine Learning, Deep Learning, Statistics, Quantitative modeling techniques).
3. Knowledge of Big Data Engineering(Hadoop Ecosystem).
4. Knowledge of Data Warehouse and Dimensional Data Modeling.
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