REQ13556 Analyst, Data Science (Open Date: 05/11/2025)
POSITION SUMMARY:
The role involves deploying state-of-the-art deep learning architectures, including convolutional and recurrent neural networks, to engineer advanced AI-driven solutions. This position requires exposure to transformer models, large language models (LLMs), and generative approaches such as GANs, with emphasis on deriving predictive and prescriptive insights from structured and unstructured data. The Analyst works closely with IT and business teams to ensure outputs inform decision-making while aligning with governance and intellectual property frameworks
PRIMARY RESPONSIBILITIES:
- Develop and deploy predictive and statistical models to extract insights from structured/unstructured datasets.
- Apply neural network architectures (transformers, CNNs, RNNs, LLMs) for natural language and sequential data.
- Conduct exploratory data analysis, feature engineering, and dimensionality reduction for insight generation.
- Use advanced optimization and hyperparameter tuning methods to enhance model accuracy.
- Implement basic MLOps practices (model validation, deployment, monitoring pipelines).
- Derive predictive and prescriptive insights from structured and unstructured data
KEY PERFORMANCE INDICATORS:
AI and data models successfully deployed. Effectiveness of MLOps pipelines and lifecycle automation. Compliance with governance and intellectual property policies. Quality of collaboration with IT and business stakeholders. Timely delivery of projects with measurable impact. Adherence to governance and compliance frameworks.
QUALIFICATIONS:
Experience
- Currently worked at a company or institution heavily involved in data science or AI projects
- Experience in data science, machine learning, or AI Experience with model prototyping, data preparation, and exploratory analysis
- Proven track record of delivering advanced analytics and AI solutions that drive measurable business outcomes
- Exposure to business-focused analytics projects
- Project-based experience applying deep learning or NLP models is advantageous
- Preferred: Familiarity with hospitality or customer-centric industries
Education
- Degree in Data Science, Artificial Intelligence, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative discipline
- Preference is given to candidates with a post graduate degree from a major, accredited institution
Skills / Competencies
- Hands-on experience with Python and deep learning frameworks.
- Familiarity with transformer-based architectures (BERT, GPT-style LLMs).
- Exposure to generative modeling (GANs, VAEs).
- Basic knowledge of MLOps concepts (CI/CD, monitoring).
- Expertise in programming and technical skills on data science and AI technologies, such as machine learning, deep learning, NLP, LLM and predictive modeling.
- Understanding of machine learning model deployment, and lifecycle management
- Strong ability in data preprocessing and feature engineering.
- Strong analytical and data interpretation skills
- Good communication and collaboration skills across technical and business domains.
- Fluency in English, Cantonese, and Mandarin.
- Ability to adapt to a fast-paced, multicultural dynamic environment.