Machine Learning Engineer

London, UK

Kingfisher

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Overview

We’re Kingfisher, A team made up of over 82,000 passionate people who bring Kingfisher - and all our other brands: B&Q, Screwfix, Brico Depot, Castorama and Koctas - to life. That’s right, we’re big, but we have ambitions to become even bigger and even better. We want to become the leading home improvement company and grow the largest community of home improvers in the world. And that’s where you come in.

 

At Kingfisher our customers come from all walks of life, and so do we. We want to ensure that all colleagues, future colleagues, and applicants to Kingfisher are treated equally regardless of age, gender, marital or civil partnership status, colour, ethnic or national origin, culture, religious belief, philosophical belief, political opinion, disability, gender identity, gender expression or sexual orientation.

 

We are open to flexible and agile working, both of hours and location. Therefore, we offer colleagues a blend of working from home and our offices, located in London, Southampton & Yeovil. Talk to us about how we can best support you!

 

We are looking for a Machine Learning Engineer to join our growing team, to develop and deploy core ML/AI algorithms required to tackle data science challenges across Kingfisher Group. You will support data science projects from start to production, developing quality code and carrying out automated build and deployments, working closely with colleagues in the Data Science team as well as stakeholders across the business. 

What's the job?

  • Develop high-quality machine learning models to solve business challenges  
  • Develop production quality code and carry out basic automated builds and deployments 
  • Write comprehensive, well written documentation that meets our needs 
  • Identify work and dependencies, tracking progress through a set of tasks 
  • Communicate clearly with colleagues and business stakeholders 
  • Proactively share ideas with colleagues and accept suggestions 
  • Ability to work on multiple data science projects and manage deliverables 

What you'll bring

  • Solid understanding of computer science fundamentals, including data structures, algorithms, data modelling and software architecture 
  • Solid understanding of classical Machine Learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, etc), state-of-the-art research area (e.g. NLP, Transfer Learning etc) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc) 
  • Solid knowledge of SQL and Python's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib, etc) 
  • Understanding of model evaluation, data pre-processing techniques, such as standardisation, normalisation, and handling missing data 
  • Solid understanding of summary, robust, and nonparametric statistics; hypothesis testing, probability distributions, sampling techniques, and stochastic processes 

 

At Kingfisher, we value the perspectives that any new team members bring, and we want to hear from you. We encourage you to apply for one of our roles even if you do not feel you meet 100% of the requirements.

 

In return, we offer an inclusive environment, where what you can achieve is limited only by your imagination! We encourage new ideas, actively support experimentation, and strive to build an environment where everyone can be their best self.

 

We also offer a competitive benefits package and plenty of opportunities to stretch and grow your career.

 

If you require any reasonable adjustments to be made during an interview, please do let us know and we’ll do what we can to help make the experience more comfortable for you.

 

Interested? Great, apply now and help us to Power the Possible.

 

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: Agile Architecture BERT Computer Science Core ML Data analysis Deep Learning Jupyter LSTM Machine Learning Matplotlib ML models NLP Pandas Python Research Scikit-learn SQL Statistics Testing XGBoost

Perks/benefits: Career development Flex hours Startup environment

Region: Europe
Country: United Kingdom
Job stats:  20  6  0

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