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? Minimum 5 years of experience in AI/ML/DL. In-depth knowledge of various classic statistical learning algorithms, neuro network, transformer-based models, and their applicability in different contexts. ? Proven expertise in any of the following areas, and with in-depth scientific understanding and experience of building related application from 0-1: ? Computer Vision ? NLP ? Timeseries ? Recommendation and search engine ? Casual inference and detection ? Ability to customize, modify and improve existing ML/DL algorithms, and rich experience in finetuning, performance uplift, and monitoring both online and offline. ? Proficiency in mainstream ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch) and advanced programming languages (e.g., Python, Java, node, etc.). ? Proven expertise in in-depth data analysis, experiment design, and feature engineering. ? Proven in-depth knowledge and experience in manipulating complex, large and distribute datasets, developing appropriate data services and applications to serve business better. ? Rich experience in leveraging modern data lake and data warehouse platforms, i.e., Hadoop, Flink, AWS redshift, Databrick. ? Solid knowledge and skills relevant for integration design and architecture thinking, flexible with design patterns like DDD/TDD to make solutions easy to be replicated and scaled, architecture fit NN business as well. ? In-depth knowledge of DevOps and methodologies. ? Experience in scientific communication and stakeholder engagement within a complex organizational setting.

Key areas of responsibility 主要工作職責(zé):

The Data Scientist has the responsibility to design, develop, and refine advanced AI and ML algorithms, applying cutting-edge techniques to process structured and unstructured data from multiple modalities. Independently handle most situations within the VP/CVP area, with minimal guidance required, and seek advice only for more complex issues. Collaborates with cross-functional stakeholders to ensure alignment of AI/ML solutions with business and scientific objectives, while maintaining adherence to Good Machine Learning Practices (GMLP). Represents the AI & ML Science cluster in discussions and projects, providing subject matter expertise and influencing decision-making within the operational area. May mentor or coach junior colleagues, contributing to the development of team capabilities and fostering a culture of innovation and excellence.

Main Job Tasks 主要工作任務(wù):

1. Design and develop advanced AI and ML algorithms: ? Create and refine machine learning models, including classification, regression, clustering, NLP, and computer vision techniques. ? Apply advanced statistical methods and programming to solve complex data challenges. Data products delivery: ? Participate in solution design stage with team, influence data architecture, framework and solutions developing in line with STJ vision of ‘digital factory’. ? Develop and refine advanced AI/ML algorithms to analyze multimodal data, driving novel insights and predictions.

2. Implement and optimize feature engineering pipelines: ? Develop robust pipelines to preprocess and transform structured and unstructured data. ? Design scalable feature engineering pipelines and leverage cloud computing to optimize data processing workflows. ? Ensure data quality and relevance for model training and evaluation.

3. Leverage cloud computing for scalable data processing: ? Utilize cloud platforms to manage large-scale data processing and model deployment.

? Ensure efficient use of cloud resources for cost-effective solutions.

4. Communicate scientific findings effectively to stakeholders: ? Present insights, predictions, and recommendations in a clear and actionable manner. ? Tailor communication to both technical and non-technical audiences.

5. Collaborate with cross-functional teams to deliver AI-driven solutions: ? Work closely with domain experts, data engineers, and business stakeholders. ? Align AI initiatives with organizational goals and project requirements.

Education Background: 教育背景

? Master's or PhD’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field ? Extensive knowledge of data science, mathematics and statistics ? Excellent command of spoken and written English