
Sales - Principal AI Scientist
- Singapore
- Permanent
- Full-time
- Model Development: Design and implement machine learning models, including traditional ML, optimization, deep learning, reinforcement learning, graph neural networks, and generative AI, to address business challenges in customer acquisition, engagement, and retention.
- Algorithm Innovation: Develop novel algorithms and optimization techniques to solve complex problems, ensuring scalability and performance in production environments.
- Model Validation: Invent and implement robust validation strategies to ensure model accuracy, reliability, and generalizability, leveraging both quantitative metrics and qualitative insights.
- Data Processing: Work with large-scale datasets, utilizing advanced data processing techniques to extract meaningful insights and prepare data for modeling.
- Productionization: Deploy and maintain machine learning models in production, ensuring high performance, scalability, and reliability.
- Multi-Functional Collaboration: Partner with sales, engineering, analytics, and other teams to align ML solutions with business objectives and integrate them into user-facing systems.
- Continuous Improvement: Stay abreast of the latest advancements in AI/ML and propose innovative approaches to enhance existing solutions.
- Professional Experience: Minimum of 10 years of professional experience in machine learning, artificial intelligence, data science, or related fields, with a proven track record of delivering impactful ML solutions in industry settings.
- Educational Background: Advanced degree (Master's or Ph.D.) in Computer Science, Data Science, Operations Research, or a related field, or equivalent professional experience.
- Operations Research Expertise: Strong background in operations research, with hands-on experience applying optimization techniques (e.g., linear programming, dynamic programming, combinatorial optimization) to solve complex, real-world problems in sales or related domains.
- Advanced AI/ML Knowledge: Deep understanding of machine learning principles, including supervised and unsupervised learning, deep learning, reinforcement learning, graph neural networks, and generative AI. Proficiency in practical implementation, hyper-parameter tuning, and performance optimization is essential.
- Algorithm Development: Exceptional ability to design and implement novel algorithms tailored to specific business needs, with a focus on scalability and efficiency.
- Validation Expertise: Proven ability to develop innovative validation frameworks to assess model performance, ensuring robustness and reliability in production environments.
- Python Proficiency: Exceptional programming skills in Python, with experience writing clean, efficient, and maintainable code. Familiarity with libraries such as TensorFlow, PyTorch, Scikit-learn, or similar is highly desirable.
- SQL Competence: Strong ability to write complex SQL queries to extract, transform, and analyze large datasets from relational databases.
- Multi-functional Collaboration: Excellent communication and collaboration skills to work effectively with diverse teams and translate business requirements into technical solutions.
- Experience with Large-Scale Systems: Practical experience building and deploying ML models at scale, with a focus on real-world applications.
- Experience with transformer-based architectures or large language models (LLMs) for personalization or other applications.
- Familiarity with cloud-based ML platforms (e.g., AWS, GCP, Azure) and distributed computing frameworks.
- Knowledge of sales and customer engagement processes, particularly in a global context.
- Ph.D. in Machine Learning, Computer Science, Mathematics, Operation Research, or a related field.