Senior Machine Learning Engineer in Yeovil

We’re Kingfisher, a team made up of over 74,000 passionate people who bring Kingfisher - and all our other brands: B&Q, Screwfix, Brico Depot, Castorama and Koctas - to life. We want to become the leading home improvement company and grow the largest community of home improvers in the world.

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.

We are looking for a Senior Machine Learning Engineer to join our growing team, to develop and deploy core ML/AI algorithms 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, track executing 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

Be Customer Focused – constantly improving our customers’ experience

• I listen to my customers
• I use available data to help make decisions

Be Human – acting with humanity and care

• I do the right thing
• I am respectful

Be Curious – thrive on learning, thinking beyond the obvious

• I build and share new ideas
• I try new things and share my learnings

Be Agile – working with trust, pace and agility

• I have courage to be creative
• Done is better than perfect, I aim for 80/20

Be Inclusive – acting inclusively in diverse teams to work together

• I embrace allyship
• I have self-awareness and a desire to learn

Be Accountable – championing the plan to deliver results and growth

• I own my actions
• I understand the Kingfisher plan and how it relates to my role

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