Junior Data Scientist
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Our client is seeking a Data Scientist to support multiple product squads in redesigning operational workflows and developing AI-enabled solutions. The role focuses on analysing large operational datasets, identifying anomalies and risk patterns, and building machine-learning models to improve decision-making and operational efficiency.
Responsibilities- Analyse large operational datasets to identify patterns, anomalies, outliers and potential risk indicators.
- Develop machine-learning models for anomaly detection, clustering, classification, segmentation and risk scoring.
- Perform feature engineering using structured and unstructured data, and evaluate model performance using appropriate metrics.
- Build and maintain scalable data pipelines and deploy production-ready models integrated with applications.
- Monitor model performance, data quality and data drift after deployment.
- Collaborate with engineers, product teams and domain experts to translate operational challenges into practical analytical solutions.
- Apply LLMs and other AI techniques alongside traditional machine-learning approaches where appropriate.
- Develop reusable analytical solutions and components for application across multiple projects.
- At least 2 years of relevant experience in data science or related field
- Degree in Data Science, Computer Science, Statistics, Machine Learning, Data Analytics, Information Systems or a related field.
- Strong proficiency in Python and SQL, with experience analysing large, complex operational or transactional datasets.
- Hands-on experience in applied data science, including statistical analysis, feature engineering, machine learning and model evaluation.
- Experience with anomaly detection, classification, clustering, risk modelling or similar techniques.
- Experience building data pipelines and deploying models into production environments.
- Familiarity with software engineering practices, including Git, automated testing and APIs
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