Data Scientist (Senior)

Key Responsibilities

• Translate business problems into data-driven and AI-enabled solutions
  
• Perform exploratory data analysis to uncover patterns issues and opportunities
  
• Design build and maintain data pipelines to support analytics and modelling use cases
  
• Develop train evaluate and iterate on machine learning and AI models
  
• Apply appropriate model evaluation techniques and define success metrics
  
• Support operational data workflows and resolve day-to-day data processing issues when required
  
• Produce clear dashboards reports and visualisations for stakeholders
  
• Communicate insights model behaviour and recommendations to both technical and business audiences
  
• Collaborate closely with data engineering AI platform and observability teams to productionise solutions
  
• Contribute to best practices around data quality governance and responsible use of AI
  

Essential Skills

• Excel SQL PowerBI AWS and quicksight
• Data analysis exploration and feature engineering (EDA)
  
• Strong applied statistics and machine learning foundations
  
• Python-based data science and ML stack (e.g. pandas NumPy scikit-learn PyTorch / TensorFlow)
  
• Data engineering skills: ETL design batch and streaming data processing
  
• Experience with distributed data systems (e.g. Kafka Spark or equivalent)
  
• SQL and structured / semi-structured data querying
  
• Experiment design model evaluation and validation techniques
  
• Dashboarding reporting and data visualisation
  
• Business problem translation and requirements understanding
  
• Version control and collaborative development (Git)
  

Advantageous Skills

• MLOps practices (model packaging deployment pipelines monitoring awareness)
  
• Data governance principles (data quality lineage ownership compliance awareness)
  
• Model evaluation performance tracking and drift detection concepts
  
• Cloud-based data and ML environments (Azure / AWS)
  
• Generative AI and LLM-based solution experience
  
• AI agent or advanced prompting familiarity
  
• Experience collaborating with observability and platform engineering teams
  
• Domain-specific knowledge aligned to business use cases