Senior Research Data Scientist

July 16

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DHL

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DHL is the leading global brand in the logistics industry$1. .$1

world leader Air Freight • Project Cargo • specialist world leader sea freight • Contract Logistics • world leader consolidator

10,000+

💰 Corporate Round on 2019-12

Description

• Create new science-based solutions that can be captured as science modules and applied across clients, with support from senior team members. • Pick up new machine learning approaches, such as regularised regression, clustering or tree-based ensembles, graph-based approaches, natural language processing and neural network techniques and apply them on client data. • Perform exploratory data analysis to characterise and visualise datasets • Extend and develop programming skills, in languages such as Python and Spark, to develop efficient science code for science modules. • Help identify new opportunities within the Data Science space for future dunnhumby solutions. • Implement advice from colleagues to resolve challenges. • Follow Quality Assurance processes, ways of working and meet coding standards. • Ensure smooth running of your projects, working with senior team members for direction. • Build strong relationships within the team and with internal stakeholders, ensuring clear and effective communication.

Requirements

• Master’s degree or equivalent in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Statistics, Physics, Engineering, Biology or related field. • Experience with machine learning techniques such as regularised regression, clustering or tree-based ensembles, and the ability to implement them through libraries. • Experience with programming, ideally Python, and the ability to quickly pick up handling large data volumes with modern data processing tools, e.g. by using Hadoop / Spark / SQL • Experience with or ability to quickly learn open-source software including machine learning packages, such as Pandas and scikit-learn, along with data visualisation technologies. • A willingness to present your work to both technical and non-technical audience and to contribute to the wider data science community.

Benefits

• Comprehensive rewards package • Flexible working hours • Birthday off • Investment in cutting-edge technology • Diversity and inclusion networks