Lead Machine Learning Engineer
London
Posted 2 months ago
Hybrid
Senior Level
Overview 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. Guided by our purpose Better Homes. Better Lives. For Everyone. We believe a better world starts with better homes, and we work every day to make that a reality. Join us and help shape the future of home improvement. We are looking for a Lead Machine Learning Engineer to join our Data Science team, to lead the research and development process of ML/AI services developed in the Group Data Science team. You will trailblaze the development of data science algorithms, while building, leading, nurturing and retaining a high performing data science team working on banner as well as group priorities. What's the job? Lead the implementation of data science projects and data science approaches to support commercial goals Develop a highly proficient team of Machine Learning Engineers, establishing collaborative ways of working Collaborate with tech, product and data teams to develop the data platforms that allow us to apply data science and embed the use of data science directly in our products and processes Support diverse teams in translating between business and data in the design of project work, and in the synthesis and communication of recommendations and results Be a champion and role model for the application of data science across the Kingfisher group Support the data leadership team in developing a “data culture” and demonstrating the value of data in our decision making Lead our efforts to develop the data science (and broader customer analytics) “brand” at Kingfisher for both internal and external audiences What you'll bring Proven experience delivering high-quality AI-based products and productionisation of Machine Learning based products Proven experience developing cloud-based machine learning services using one or more cloud providers (preferably GCP) Excellent understanding of classical Machine Learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.) Strong knowledge of SQL and Python's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib) Strong software development skills (Python is the preferred language) Proven experience in deploying ML/AI services suing Kubernetes & KubeFlow Strong management and leadership skills – previous experience managing a team Strong influencing, communication and stakeholder management skills How We Work We believe in flexibility and balance. Our hybrid model blends home working for focus with time spent connecting and collaborating - whether in our offices or at offsite locations. On average within our Engineering team - 40% of your time involving in-person collaboration. We value the perspectives new team members bring and encourage you to apply - even if you don’t meet 100% of the requirements. What We Offer An inclusive environment where your potential is limited only by your imagination. We encourage new ideas, support experimentation, and strive to create a workplace where everyone can be their best self. Find out more about Diversity & Inclusion at Kingfisher here We also offer a competitive benefits package and plenty of opportunities to stretch and grow your career. Scroll down below to find out more about our benefits. Diversity & Inclusion Our customers come from all walks of life - and so do we. We’re committed to ensuring all colleagues, future colleagues, and applicants are treated equally, regardless of age, gender, marital or civil partnership status, ethnicity, culture, religion, belief, political opinion, disability, gender identity, gender expression, or sexual orientation. Interested? Great, apply now and help us to Power the Possible. #LI-TB1
Skills
Machine Learning
Data Science
Cloud Computing
Python
SQL
Kubernetes
Leadership
Communication
Stakeholder Management
Customer Focus
Agility
Inclusivity
Accountability
Deep Learning
Data Analysis
Collaboration
Location
London