Senior Data Scientist

Job Description:

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 (23 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 (24 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)

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