• 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 主要工作职责:

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 主要工作任务:

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