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Senior Data Scientist

Summary

Build and validate AI/ML models for financial services, focusing on rapid prototyping, LLM techniques, and end-to-end ML/DL development in a fast-paced, agile environment.

Senior AI/ML Data Scientist – Innovation & Model Development

Key Responsibilities

  • Track latest AI/ML developments (LLMs, architectures, emerging techniques) and assess relevance to business use cases
  • Evaluate feasibility of AI solutions and recommend optimal technical approach
  • Build rapid POCs (2–3 days) to validate ideas before investment
  • Benchmark vendor and open-source solutions with clear comparison and recommendations
  • Design and develop ML/DL models end-to-end (algorithm selection, feature engineering, optimisation)
  • Deliver prototypes within short timelines (2–4 weeks) with strong validation standards
  • Ensure model performance, robustness, and bias checks
  • Use generative AI tools (e.g. Copilot, ChatGPT, Claude, Cursor) to accelerate prototyping and development
  • Collaborate with product, business, and engineering teams in an agile environment
  • Support junior team members through mentoring, code reviews, and knowledge sharing

Skills & Experience

  • 7+ years of experience in Data Science / Machine Learning
  • Proven experience in banking or financial services
  • Strong expertise in ML/DL (supervised, unsupervised, NLP, time series)
  • Hands‑on experience with Python (scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM)
  • Solid understanding of LLMs and modern techniques (fine‑tuning, RAG, prompt engineering, agents)
  • Strong foundation in statistics, EDA, feature engineering, and model evaluation
  • Experience with SQL and large‑scale data processing
  • Exposure to cloud ML platforms (AWS, Azure, or GCP)
  • Familiarity with Git, Jupyter, Databricks

Preferred Skills & Attributes

  • Experience in Computer Vision, Reinforcement Learning, or Graph ML
  • Strong analytical thinking and problem solving
  • Ability to simplify complex topics into clear recommendations
  • Critical mindset towards model outputs and AI-generated code
  • Pragmatic, with focus on speed and business impact
  • Strong communication and stakeholder management
  • Comfortable working in ambiguity
  • Proactive, with ownership and mentoring mindset

Work Environment

  • Agile, fast‑paced innovation environment
  • Close collaboration with business, product, and engineering teams
  • Focus on rapid experimentation and delivery of AI solutions
  • English‑speaking environment (fluency required)

Work Location

Putrajaya (Fully onsite role)

See also

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