Data Science Innovation Lead
3 weeks ago
About dunnhumby
dunnhumby is a pioneering force in Customer Data Science, empowering businesses to thrive in today's data-driven economy. We put the customer first and drive growth through cutting-edge analytics.
Our Mission
We enable businesses to innovate and transform themselves by becoming champions for their customers. With a deep heritage in retail and expertise in multi-dimensional data, we now help companies across industries become customer-first.
With over 2,500 experts in offices worldwide, working with iconic brands like Tesco, Coca-Cola, Meijer, Procter & Gamble, and Metro, we're shaping the future of customer-led business.
The Role
We're looking for a seasoned Research Data Scientist who will elevate our science capabilities. As a key player, you'll work with passionate experts to apply machine learning and statistical techniques to complex business problems. You'll contribute to research, implementation, and validation of new approaches, presenting results to internal stakeholders.
Your focus will be on creating science solutions that can be delivered across clients and engineered into modules. This involves developing new ideas, picking up emerging machine learning techniques, and applying them to client data. You'll also perform exploratory data analysis, extend programming skills, and identify opportunities within the Data Science space.
Responsibilities
- Create innovative science-based solutions that can be captured as science modules and applied across clients.
- Pursue 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.
- Enhance and develop programming skills in languages like 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.
- Adhere to Quality Assurance processes, ways of working, and coding standards.
- Ensure smooth project running, working with senior team members for direction.
- Bolster strong relationships within the team and with internal stakeholders, ensuring clear and effective communication.
Collaboration
You'll primarily work with:
- Applied and Research Data Scientist teams.
- Data Science Engineering teams.
- Product and Client teams where required.
Requirements
To succeed in this role, you'll need:
- A Master's degree or equivalent in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Statistics, Physics, Engineering, Biology, or a related field.
- Experience with machine learning techniques, such as regularised regression, clustering or tree-based ensembles, and the ability to implement them using libraries.
- Proficiency in programming, ideally Python, and the ability to quickly grasp handling large data volumes with modern data processing tools, e.g., Hadoop/Spark/SQL.
- Familiarity with open-source software, including machine learning packages like Pandas and scikit-learn, along with data visualisation technologies.
- A willingness to present your work to technical and non-technical audiences and contribute to the wider data science community.
- A PhD in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Statistics, Physics, Engineering, Biology, or a related field (desirable).
- Experience in the retail sector (desirable).
What We Offer
At dunnhumby, we won't just meet your expectations – we'll defy them. Our comprehensive rewards package includes competitive compensation, flexible working hours, and thoughtful perks. You'll benefit from an investment in cutting-edge technology and enjoy a culture of diversity and inclusion.
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