Research Data Scientist

Responsibilities

• Translate complex business problems into data science problems and solve them using scalable, state-of-the-art AI algorithms
• Prototype solutions using Python and Spark to facilitate the development and testing of algorithms on large datasets
• Research the latest machine learning approaches to identify new opportunities for future solutions
• Apply and extend experimental design methodology to conduct rigorous measurement of treatment effects
• Utilize machine learning techniques for applications in classification, prediction, and clustering

Requirements

• Degree or equivalent in a statistical or mathematical subject
• 2-5 years of experience in Data Science
• Strong understanding of statistics and mathematical methodologies, including forecasting, regression, linear models, time series, and optimization
• Proficiency in Python and Spark
• Experience with SQL and both relational and non-relational databases
• Familiarity with machine learning libraries such as Pandas, SciPy, Scikit-learn, and TensorFlow
• Solid grasp of Object-Oriented Programming (OOP)
• Experience using algorithms at scale, such as Ancova, random forests, or XGBoost

Benefits

• Comprehensive rewards package typical of a leading technology company
• Personal flexibility and agile working opportunities
• Flexible working hours and your birthday off
• 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 for their customers.