Data Scientist

As a Data Scientist you will play a crucial part in managing, innovating and optimising our core AI systems and large scale product catalogue (Data feed). Working heavily within DataBricks and Google Cloud Platform, you will focus on enriching our product catalogue feeds, building scalable machine learning solutions and driving continuous improvement in our automated capabilities.

Rather than standard reporting, the focus of this Data Scientist role is to actively innovate on how we process, optimise and leverage data feeds to drive business value across NEXT.

We are looking for someone with a strong grasp of data science techniques who can build robust models while communicating findings and new AI strategies effectively to various stakeholders.

What You’ll Take On:

• Innovate and optimise complex data feeds, ensuring high quality, relevance and performance of our data feeds and pipelines.
• Collaborate with teams from around the business to understand problems, identify automation opportunities and gather requirements for modelling and advanced analytics.
• Proactively develop systems detecting trends and anomalies within large data streams, creating presentations or automated reports to recommend algorithmic or business logic improvements.
• Work closely with data engineers to improve the data collection process (data ingestion & ETL pipelines) and support initiatives for data integrity, normalisation and scalability.
• Build, deploy, monitor and maintain ML Models. Key use cases include feed optimisation, recommendation algorithms, classification tasks, predictive analytics and MLOps deployments.
• Continuously evaluate the effectiveness of our models and feed logic, providing recommendations for architecture improvements and performance optimisation.

• Proven years of Data Science experience related to the retail, eCommerce or consumer tech industries (3-4 years).
• Good analytical & problem-solving skills and excellent attention to detail.
• Understanding and experience of data science techniques covering statistical analysis, A/B testing, time-series, regression, classification and optimisation problems.
• Proficient in SQL & Python. Familiarity with data manipulation libraries (e.g. PySpark, Pandas, Numpy) and machine learning frameworks (e.g. scikit-learn, TensorFlow or PyTorch).
• Experience with MLOps tools (e.g., MLflow, Databricks Model Registry, Unity Catalog, Vertex AI) and version control (Git).
• Strong coding practices with experience in code optimisation, ETL frameworks and processing large-scale data feeds.
• Good time management skills with the ability to manage multiple deadlines, priorities and iterative product developments.
• High-level written and verbal communication skills. Ability to convey complex algorithmic or technical findings to non-technical audiences.
• Ability to visualise data in Data Studio/Looker Studio or PowerBI.
• A proactive innovator who is willing to learn different technologies and analytical platforms to improve our tech stack.

Desirable / Nice to Have

• Experience working with Large Language Models (LLMs) and agentic workflow frameworks (e.g. LangGraph, LangChain).
• Experience developing custom evaluation harnesses to test and validate AI model outputs.
• Familiarity with Retrieval-Augmented Generation (RAG) architectures or fine-tuning open-source models.