Data Scientist

HKT’s Data Monetisation Team is seeking a highly capable Data Scientist / Senior Data Scientist to drive end-to-end AI and analytics initiatives—from business problem framing and insight generation to building and deploying scalable machine learning and AI solutions.

This role is suited for candidates with deep expertise in at least one of the following areas: Business Strategy & Analytics, LLM/GenAI, Reinforcement Learning, or MLOps. You are not expected to cover all domains but should bring strong depth in one area and collaborate effectively across others.

You will contribute to the transformation of complex data into robust, interpretable models and actionable solutions that enhance customer experience, enable personalization, and support business growth.

Responsibilities

• Lead or contribute to data science initiatives aligned with your area of expertise (e.g., business analytics, LLM/GenAI, RL, or MLOps).
• Collaborate with stakeholders to understand business problems and translate them into analytical approaches, models, and measurable KPIs.
• Perform deep-dive data analysis to uncover trends, patterns, customer behaviors, and business opportunities across digital channels and product journeys.
• Translate analytical findings into clear, actionable insights and strategic recommendations.
• Design, build, and optimize machine learning and AI solutions based on your specialization.

Specialized responsibilities (depending on expertise):

• Develop and optimize Retrieval-Augmented Generation (RAG) pipelines, including embedding, retrieval, re-ranking, and prompt engineering.
• Implement agentic AI and reinforcement learning models for personalization and conversion optimization.
• Build and maintain scalable ML pipelines, including automation of training, testing, and deployment (MLOps).
• Apply guardrails, evaluation frameworks, and A/B testing to ensure model quality and performance.
• Support model evaluation, experimentation (e.g., A/B testing), and ongoing performance monitoring.
• Collaborate cross-functionally to deliver end-to-end data products and productionized solutions.
• Contribute to deployment, scalability, and reliability of data science systems in production environments.

Requirements

• Bachelor’s or advanced degree (Master’s/PhD preferred) in Machine Learning, Data Science, Computer Science, Statistics, Mathematics, Economics, or a related field.
• 3–5+ years of experience in data science, machine learning, or advanced analytics (candidates with more experience may be considered for Senior level).
• Demonstrated expertise in at least one of the following domains:
• Business Strategy & Analytics (e.g., KPI design, stakeholder engagement, insight generation)
• LLM / GenAI (e.g., RAG pipelines, prompt engineering, vector databases)
• Reinforcement Learning / Personalization (e.g., agent-based systems, optimization models)
• MLOps (e.g., ML pipelines, deployment, monitoring, lifecycle management)
• Strong proficiency in Python and SQL.
• Solid understanding of statistics, experimentation, and model evaluation.
• Experience working with cloud platforms (AWS, Azure, GCP) and large-scale data systems is a plus.
• Experience in Telecom, Retail, FMCG, or Property sectors is a plus; familiarity with Martech and personalization is advantageous.
• Strong communication skills with the ability to translate technical concepts into business impact.
• Proactive, detail-oriented, and able to manage multiple initiatives in a fast-paced environment.
• Strong sense of ownership and a collaborative, team-oriented mindset.

About the Team

The Data Monetisation Team at HKT manages customer data and transforms it into actionable insights that drive business growth. We develop end-to-end AI solutions and embed them seamlessly into business processes.

We are a team of 40+ data scientists and engineers committed to building a data-driven culture through a single source of truth and democratized data access. We value ownership, open communication, and continuous learning while solving real-world business challenges with cutting-edge AI technologies.