HCLTech Hiring! Full Time AI Senior Data Scientist in Federal Territory - Ricebowl

About the role

HCL Tech is seeking a motivated and talented AI Senior Data Scientist to join our team in Kuala Lumpur. As a Senior Java Developer, you will be responsible for designing, developing, and maintaining high-quality software applications using Java technologies. This full-time position offers the opportunity to work on cutting-edge projects and collaborate with a dynamic team of professionals.

What you'll be doing

As part of IT Innovation projects, you will join the AI Factory/Innovation team as a Senior Data Scientist with a dual strategic role: technology watch and AI model development.

Mission 1 – Technology watch and feasibility: You will be the technical reference for new AI/ML approaches (LLMs, new architectures, emerging techniques). You will assess the technical feasibility of business use cases, benchmark market solutions (vendors, open-source), and deliver quick POCs (2–3 days) to validate hypotheses before major investment.

Mission 2 – AI model development: You will design and develop ML/DL models for selected use cases, from algorithm selection to final optimisation. You will build rapid prototypes (POCs in 2–4 weeks) and support a junior Data Scientist in developing their skills.

As a vibe coding expert, you use generative AI tools (GitHub Copilot, Cursor, Claude, ChatGPT) to accelerate data exploration, model prototyping, analysis code generation and documentation, while maintaining a critical mindset regarding the results.

You will work in an agile mode, closely with the Products & Innovation business teams, AI developers, architects and other Data Scientists.

Targeted profile: Senior Data Scientist with banking/finance experience, expert in ML/DL and proficient in vibe coding, able to quickly assess the technical feasibility of AI use cases, develop POCs, and stay at the forefront of technological advances.

Technology watch and feasibility:

• Weekly technology watch on AI advances (papers, new approaches, tools)
• Rapid technical feasibility assessments of business use cases (2–3 days max)
• Benchmark of market solutions (vendors vs open-source) with decision matrix
• Quick POCs to validate hypotheses before major investment
• Clear and actionable technical recommendations for decision-makers
• Participation in business workshops to understand needs

AI model development:

• Design and development of ML/DL models for priority use cases
• Justified choice of algorithms and technical approaches (baseline, state-of-the-art)
• Feature engineering and model optimisation (performance, robustness)
• Rapid prototyping using vibe coding (POC in 2–4 weeks)
• Rigorous validation of models (metrics, robustness, bias)
• Comprehensive technical documentation (notebooks, methodology, results)
• Collaboration with AI developers for industrialisation

Mentoring and knowledge sharing:

• Support to the junior Data Scientist (pair programming, code reviews)
• Knowledge transfer on advanced techniques and best practices
• Sharing of technology watch findings with the team (tech talks, documentation)
• Contribution to the library of prompts and vibe coding techniques
• Facilitation of technical workshops and feedback sessions

What we're looking for

• Bachelor's or Master degree in information technology or equivalent

• At least 7 years of experience in Data Science / Machine Learning

• Proven experience in the banking/finance sector (understanding of business challenges)
• Demonstrated experience in vibe coding with productive use of AI tools for rapid prototyping
• Expertise in ML/DL: supervised learning, unsupervised learning, deep learning, NLP, time series
• Proficiency in Python frameworks: scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM
• In-depth knowledge of LLMs and modern techniques (fine-tuning, RAG, prompt engineering, agents)
• Expertise in feature engineering and variable selection
• Strong skills in exploratory data analysis and statistics
• Experience in model evaluation and optimisation (hyperparameter tuning, cross-validation)
• Knowledge of Cloud ML platforms (AWS SageMaker, Azure ML, GCP Vertex AI)
• Proficiency in SQL and handling large-scale datasets
• Knowledge of version control tools (Git) and notebooks (Jupyter, Databricks)
• Nice to have: Experience in Computer Vision, Reinforcement Learning or Graph ML