About the Team:
Within Tesco Data & Analytics, we help our customers and the communities where we operate get the most value from data. We build and run Tesco’s data platforms, we architect and engineer data onto these platforms, provide capabilities and tools to the analytics community across Tesco, develop data products at scale and maintain existing applications.
Our Data Science team are involved in a broad range of projects, spanning across supply chain, logistics, store and online. These include projects in the areas of Operations Optimizations, Commercial Decision Support (e.g. Forecasting, Range Optimization, Supply Chain support), Online (e.g. Search and Recommendation) and Intelligent Edge (e.g. Computer Vision). Our Machine Learning Engineers work alongside our data scientists, helping with everything from development of tools and platforms, code optimization through to deployment of solutions on the edge, cloud and big-data environments.
What is in it for you Salary:
UoP: 18 000 - 24 000 PLN gross/monthB2B: 20 000 - 27 000 PLN net/month
Hybrid working
We always welcome conversations about flexible working, so feel free to talk to us during your application about how we can support you. We value connecting, collaborating, and innovating with our colleagues in person.
At Tesco Technology, we work in a hybrid model. This role requires you to be based in or near Kraków, as we currently meet in the office 3 days a week.
Benefits
Tesco is a diverse and exciting employer, dedicated to being #aplacetogeton, providing career-defining opportunities to all of our colleagues. If you choose to join our business, we will provide you with (for all):
- Permanent contract from the go – as a sign of our trust in your abilities
- MacBook as your tool for work
- Learning opportunities - certified technical training and learning platforms like Udemy, Pluralsight and O’reily
- Referral Bonus
- Sports activities with a personal trainer in the office
- Additional 4 days of paid leave to support your well-being and family life
- Up to 20% yearly salary bonus – based on both individual and business performance
- Private healthcare (LuxMed)
- Cafeteria & Multisport
- Supporting those, who are not yet eligible for full holiday entitlement, by expanding their pool from 20 to 25 days
- Relocation Help
- IP Tax Deductible Costs
Tesco is committed to celebrating diversity and everyone is welcome at Tesco. As a Disability Confident Employer, we’re committed to providing a fully inclusive and accessible recruitment process, allowing candidates the opportunity to thrive and inform us of any reasonable adjustments they may require. You will be responsible for • Participating in group discussions on system design and architecture • Working with product teams to communicate and translate needs into technical requirements • Working alongside our Data Scientists, Software Engineers and Product teams across the software lifecycle • Delivering high quality code and solutions, bringing solutions into production • Performing code reviews to optimize technical performance of data science solutions. • Supporting production systems, resolving incidents, and performing root cause analysis • Look for how we can evolve and improve our technology, processes and practices • Sharing knowledge with the immediate engineering team • Collaborate with other teams on more complex initiatives via working groups • Applying SDLC practices to create and release robust software
You will need You come from either an Engineering or Data Science background, with a good understanding of the Data Science Toolkit (Programming, Machine Learning, MLOps etc) and bringing data science solutions into production. You therefore tick the majority of the following points:
Key Requirements: • A higher degree in engineering, computer science, maths or science. • Customer focus with the right balance between outcome delivery and technical excellence.The ability to apply technical skills and know-how to solving real world business problems. • Demonstrable experience of building MLOps systems according to the best market standards. • Commercial experience contributing to the success of high impact Data Science projects within complex organisations. • Awareness of emerging MLOps practices and tooling would be an advantage e.g. feature stores and model lifecycle management. • knowledge of ML workflow/orchestration platform like Airflow• An analytical mind set and the ability to tackle specific business problems. • Experience with different programming languages and a good grasp of at least one language. The ideal candidate is fluent in Python. • Use of version control (Git) and related software lifecycle tooling. • Experience with tooling for monitoring, logging and alerting e.g. Splunk or Grafana. • Understanding of common data structures and algorithms. • Experience working with open-source Data-Science environments. • Knowledge of open source big-data technologies such as Apache Spark. • Experience building solutions that run in the cloud, ideally Azure. • Experience with software development methodologies including Scrum & Kanban. • A background or strong understanding of the retail sector, logistics and/or ecommerce would be advantageous but is not required.
Unsure if you fit all the criteria? Apply and give us the chance to evaluate your potential – you could be the perfect fit!
About us Tesco is a leading multinational retailer, with more than 330 000 colleagues. Our software is used by millions of people across several countries every day. Whether it’s the tills and websites our customers use, or the systems our colleagues and partners use, you’ll play your part in keeping it running like a well-oiled machine. And when a business problem pops up? You and the creative minds in our team will be challenged to solve it. As Tech Hub we cooperate within the group of Tesco Technology Hubs located in the UK, Poland, Hungary, Czech Republic and India. What our colleagues like the most at Tesco:
- We develop our own products
- We make an impact; large scale of operation
- Accountability and respect are given to us
- We cooperate and support each other
- There are great colleagues who are divided into small teams here
- We can develop and learn new things