AI Data Scientist

About the role

The AI Data Scientist will translate business requirements into data, feature engineering and modelling approaches for AI use cases, developing and improving machine learning and statistical models that are accurate, robust and aligned with business outcomes.

Key responsibilities

• Translate business and solution designs into data, feature and modelling requirements.
• Explore, clean and curate structured and unstructured data for AI use cases.
• Design and engineer features and datasets for model development and validation.
• Build, train, tune and evaluate machine learning, statistical and predictive models.
• Benchmark models against baselines, third‑party solutions and alternative methods.
• Document model assumptions, methodology, data sources and testing results.
• Collaborate with engineers and technology teams to integrate models into production.
• Support model deployment, monitoring, drift detection and continuous improvement.

Required profile

• Hands‑on experience in data science, machine learning or advanced analytics.
• Bachelor’s degree in a quantitative discipline; master’s degree advantageous.
• Proven track record of developing, evaluating and deploying models for business use.
• Ability to work quickly and accurately in a fast‑moving, commercially focused environment.

Required skills

• Python, R, SQL.
• Machine‑learning libraries such as scikit‑learn, PyTorch, TensorFlow, XGBoost.
• Feature engineering, model selection, tuning, validation and performance evaluation.
• Understanding of supervised/unsupervised learning, classification, regression, clustering and anomaly detection.
• Familiarity with generative AI, large language models and model evaluation.