Data Scientist

Key Responsibilities:

• Collaborate directly with business users and stakeholders to understand requirements and translate business problems into data science use cases.
• Analyse, clean, and prepare large, complex datasets for exploratory analysis and model development.
• Design and implement feature engineering, statistical analysis, and machine learning solutions to support business objectives.
• Develop, test, and validate data science models using Python and relevant data science libraries.
• Build scalable, production-ready data science solutions and support deployment into operational systems.
• Implement and maintain model deployment pipelines, including version control, CI/CD, and monitoring, in line with DevOps and ModelOps best practices.
• Monitor model performance, data drift, and operational metrics, and continuously optimise models in production.
• Work closely with data engineering and platform teams to leverage enterprise data platforms and cloud infrastructure.

Requirements:

• Strong proficiency in one or more data science domains, including:

1. Feature engineering
2. Statistical analysis
3. Machine learning
4. Optimisation techniques

• Strong proficiency in Python and common data science libraries (e.g. pandas, NumPy, scikit-learn, etc.).
• Proficiency in data wrangling and data processing tools and languages such as SQL and/or Apache Spark.
• Proven experience analysing large datasets and preparing data for data science and machine learning model development.
• Hands-on experience developing and deploying data science solutions into production environments.
• Working knowledge of DevOps / ModelOps principles, processes, and tools (e.g. Git, GitLab CI/CD).
• Experience working directly with users or stakeholders to iteratively deliver data science solutions aligned to business needs.

Preferred Skills:

• Experience building production-grade machine learning models, including:

1. Model performance monitoring
2. Model retraining pipelines
3. Optimisation for scalability and reliability

• Domain experience or strong interest in marketing, advertising, or performance marketing analytics.
• Experience working with cloud platforms, preferably Amazon Web Services (AWS).
• Experience with enterprise data platforms and integrated analytics solutions, preferably Databricks.
• Experience in developing, deploying, or operating Generative AI / Large Language Model (LLM) solutions in production environments.