HKT’s Data Monetisation Team is looking for a highly capable Data Scientist / Senior Data Scientist specializing in MLOps to design, deploy, and manage scalable end-to-end machine learning systems, playing a critical role in ensuring reliable, production-ready AI that drives business operations and decision-making.
Responsibilities
- Assist Lead Data Scientist in building and maintaining end-to-end ML pipelines.
- Deploy machine learning models into production environments.
- Automate model training, testing, validation, and deployment workflows.
- Monitor model performance, data drift, and system reliability.
- Manage model versioning, experiment tracking, and reproducibility.
- Ensure scalability, security, and compliance with ML infrastructure.
- Troubleshoot production issues across data, models, and infrastructure.
Requirements
- A master’s degree or PhD in Statistics, Machine Learning, Mathematics, Computer Science, Economics, or any other related quantitative field. The equivalent of the same working experience is also acceptable for the position.
- 5+ years of working experience in a data science capacity. No preference for the background sector, but a first experience in Retail/FMCG/Property/Telecom is a plus. You will also have a demonstrated and successful experience leading a data science team through the implementation of new data science models, tools, and techniques that lead to improvement if business performance due to a continued culture of informed decision-making. Strong technical understanding of Martech, personalization, and marketing automation is preferred.
- Extensive experience solving analytical issues through quantitative approaches and machine learning methods as well as vast experience using advanced statistical methods, data mining techniques, and information retrieval. A suitable candidate will show comfort analyzing and manipulating large, complex, high-dimensional data from numerous sources. Proficiency with data mining, mathematics, and statistical analysis. Advanced pattern recognition and predictive modeling experience
- Excellent communication skills to be able to tailor and convey technical messages in a clear and understandable manner, leading to business-wide improvement of data management, informed decision making, and ultimate improvement in performance.
- Experience working with distributed computing tools such as Hadoop & Spark as well as experience working in a cloud environment such as AWS, Azure or GCP.
- Hands-on experience with MLOps, ML pipeline automation, or model deployment.
- Good understanding of machine learning model lifecycle management.
- Strong Python and SQL proficiency.
- Experience with NLP, RAG, and reinforcement learning.
- Take ownership of tasks assigned and have a positive “can-do” attitude
- Curious minded and is not afraid of asking questions and challenging status quo
- Good communication skills
- A team player
About the Data Monetisation Team at HKT
The Data Monetisation Team manages customer data at HKT and is responsible for transforming data into actionable insights that support business growth. We work closely with both internal business functions and external partners to deliver values to business by applying cutting edge AI and machine learning algorithms. We excel at delivering end-to-end solutions that embedded into processes seamlessly for our users.
We are a team of 40 strong data scientists and data engineers who believe in data. We are nurturing a data-driven decision-making culture in the entire organization by creating single source of truth and democratizing data for users at all levels in the organization.
We value ownership and encourage candid communication and feedback within the team. We challenge each other so that we can find the best solution to the problem. We enjoy learning from each other and solving real world problems. Senior Data Scientist specializing in Reinforcement Learning to drive the development of intelligent, data-driven hyper-personalization. This role will focus on designing and deploying RL models, enabling advanced agentic AI use cases, and translating complex data into actionable strategies that improve customer engagement, personalization, and business performance.
