Research Data Scientist

Responsibilities

• Create new science-based solutions and modules focused on insight automation and product assortment
• Apply machine learning approaches including regularised regression, clustering, tree-based ensembles, NLP, and neural networks
• Perform exploratory data analysis to characterize and visualize complex datasets
• Develop efficient science code using Python and Spark to handle large data volumes
• Identify new opportunities within the Data Science space for future business solutions
• Collaborate with Applied Data Science, Engineering, and Product teams to deliver client value

Requirements

• Master's degree in Computer Science, AI, Machine Learning, Statistics, Physics, Engineering, Biology, or a related field
• Experience implementing machine learning techniques such as regularised regression, clustering, or tree-based ensembles
• Proficiency in Python and experience with modern data processing tools like Hadoop, Spark, or SQL
• Experience with open-source libraries including Pandas and scikit-learn
• Ability to present technical findings to both technical and non-technical audiences

Preferred Qualifications

• PhD in a quantitative field (Computer Science, AI, Statistics, Physics, etc.)
• Previous experience working within the retail sector

Benefits

• Comprehensive rewards package typical of a leading technology company
• Flexible working hours and personal flexibility
• Birthday off as a thoughtful perk
• Access to cutting-edge technology and an environment that encourages experimentation

About the Company

dunnhumby is the global leader in Customer Data Science, partnering with the world’s most ambitious retailers and brands to put the customer at the heart of every decision. We combine deep insight, advanced technology, and close collaboration to help our clients grow, innovate, and deliver measurable value.