Data Scientist

HCLTech

Putrajaya

On-site

MYR 180,000 - 280,000

Full time

7 days ago
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Job summary

HCLTech in Malaysia is seeking a senior Data Scientist to lead AI model development for prioritized business use cases. You will perform technology watch, rapid feasibility assessments, and benchmark market solutions to drive decisions.

You will design and validate ML/DL models, perform feature engineering, and deliver rapid prototypes within tight timelines. Collaboration with AI teams and knowledge sharing are key.

Qualifications

  • Requires a Bachelor’s or Master’s in Information Technology or equivalent.
  • Minimum 7 years of experience in Data Science and ML.
  • Experience in banking/finance domain with regulatory understanding.
  • Proficiency in vibe coding and rapid prototyping for AI.
  • Strong ML/DL expertise across supervised/unsupervised, NLP, time-series.

Responsibilities

  • Conduct technology watch on AI advancements and research
  • Perform rapid feasibility assessments for business use cases (2–3 days)
  • Benchmark market solutions using decision matrices
  • Develop quick POCs to validate hypotheses
  • Provide clear, actionable technical recommendations for decisions
  • Participate in business workshops to understand objectives and constraints
  • Design and develop ML/DL models for prioritized business use cases
  • Collaborate with AI developers to support deployment

Skills

Machine Learning
Deep Learning
NLP
Time-series analysis
Python
scikit-learn
TensorFlow
PyTorch
XGBoost
LightGBM
LLMs
RAG
Prompt engineering
Feature engineering
EDA
SQL
Git
Jupyter
Databricks
AWS SageMaker
Azure ML
GCP Vertex AI
Banking domain knowledge

Education

Bachelor’s or Master’s in Information Technology or equivalent

Tools

Git
Jupyter
Databricks

Job description

Key Responsibilities
Technology Watch & Feasibility
  • Conduct regular technology watch on AI advancements, including research papers, emerging techniques, and new tools
  • Perform rapid technical feasibility assessments for business use cases within short timelines (2–3 days)
  • Benchmark market solutions by comparing vendor offerings and open‑source alternatives using decision matrices
  • Develop quick proof‑of‑concepts (POCs) to validate hypotheses prior to significant investment
  • Provide clear, actionable technical recommendations to support decision‑making
  • Participate in business workshops to understand objectives, constraints, and potential AI applications
AI Model Development
  • Design and develop machine learning and deep learning models for prioritized business use cases
  • Select and justify appropriate algorithms and technical approaches, from baseline to state‑of‑the‑art solutions
  • Perform feature engineering and model optimization to enhance performance, robustness, and reliability
  • Deliver rapid prototypes using vibe coding methodologies within 2–4 weeks
  • Ensure rigorous model validation, including performance metrics, robustness checks, and bias assessment
  • Produce comprehensive technical documentation covering methodology, experiments, and results
  • Collaborate closely with AI developers to support solution industrialization and deployment
Mentoring & Knowledge Sharing
  • Provide hands‑on support to junior Data Scientists through pair programming and code reviews
  • Facilitate knowledge transfer on advanced AI techniques, tools, and best practices
  • Share technology watch insights with the team via documentation, presentations, and technical talks
  • Contribute to and evolve a shared library of prompts and vibe‑coding techniques
  • Lead technical workshops and feedback sessions to promote continuous learning and improvement
Skill Requirements
  • Bachelor’s or Master’s degree in Information Technology or an equivalent field
  • Minimum of 7 years’ experience in Data Science and Machine Learning
  • Proven experience within the banking or finance sector, with understanding of business and regulatory challenges
  • Demonstrated expertise in vibe coding, leveraging AI tools for rapid prototyping and productivity
  • Strong expertise across ML/DL techniques, including:
  • Supervised and unsupervised learning
  • Deep learning, NLP, and time‑series analysis
  • Proficiency in Python and key ML frameworks:
  • scikit‑learn, TensorFlow, PyTorch, XGBoost, LightGBM
  • In‑depth knowledge of Large Language Models (LLMs) and modern approaches:
  • Fine‑tuning, Retrieval‑Augmented Generation (RAG), prompt engineering, and agents
  • Advanced skills in feature engineering and variable selection
  • Strong foundation in exploratory data analysis (EDA) and statistics
  • Experience with model evaluation and optimisation, including hyperparameter tuning and cross‑validation
  • Hands‑on experience with cloud‑based ML platforms (AWS SageMaker, Azure ML, GCP Vertex AI)
  • Proficiency in SQL and working with large‑scale datasets
  • Experience with version control and data science tools:
  • Git, Jupyter, Databricks
  • Nice to have: Exposure to Computer Vision, Reinforcement Learning, or Graph ML
  • Malaysian candidates preferred
Soft Skills & Professional Attributes
  • Strong intellectual curiosity with an active technology‑watch mindset
  • Ability to synthesize complex technical concepts into clear, actionable recommendations
  • Critical and analytical approach to model outputs and AI‑generated code
  • Pragmatic decision‑making with focus on ROI and business impact
  • High level of scientific rigor in experimentation, validation, and documentation
  • Excellent communication skills, both technical and business‑oriented
  • Comfort working in ambiguous and evolving environments
  • Proactive mindset with the ability to initiate ideas and make proposals
  • Strong mentoring and pedagogical skills, supporting junior Data Scientists
  • Agile, adaptive, and collaborative working style
Must Have Skills
  • Phyton
  • Machine Learning and Statistical modeling
  • MS SQL
  • TensorFlow
  • Pytorch
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