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- Tasks: Lead the design and development of innovative data science solutions to drive eCommerce growth.
- Company: Join NEXT, a leading FTSE-100 retail company with a global presence.
- Benefits: Enjoy 25% off products, performance bonuses, and access to health and wellbeing services.
- Why this job: Make a real impact by using cutting-edge machine learning techniques in a dynamic environment.
- Qualifications: BSc, MSc, or PhD in a relevant field with proven data science experience.
- Other info: Flexible working options and excellent career development opportunities await you.
The predicted salary is between 43200 - 72000 £ per year.
Our eCommerce Data team are hiring a Lead Data Scientist to be at the forefront of our global growth! Based from NEXT Head Office in Leicester!
The role eCommerce Data provides the department and the business the means to see what is working and what is not by drawing data and analysing patterns of shopping on our site and in general.
As a Lead Data Scientist at NEXT you will build data driven solutions through state of the art Machine learning techniques in order to maximise the profitability.
What You'll Take On
- Proactively lead the design, development, and deployment of data science solutions.
- Working with teams from around the business to understand problems and opportunities and gather requirements for model building.
- Interrogating large volumes of data from a range of sources, including transactional, demographic and online, to collect data for modelling.
- Building predictive models and segmentations to improve profitability and improve the customer experience.
- Working with the commercial teams to implement tests to prove the value of predictive models.
- Proactively identifying opportunities for personalisation and improvements to the customer experience.
- Present outcomes to senior leadership teams and work with stakeholders across the eCommerce team to move towards shared business goals.
What You'll Bring
- BSc, MSc, or PhD in Statistics, Mathematics, Computer Science, or a related field.
- Proven years of experience in Data Science, with a focus on personalisation or recommendation systems.
- Proven leadership experience with the ability to guide projects from conception to deployment.
- Advanced proficiency in PyTorch or TensorFlow.
- Strong proficiency in SQL, Python, and distributed processing (PySpark).
- Strong communication skills with the ability to translate complex data insights into actionable business strategies.
We aim to support all candidates during the application process and are happy to provide workplace adjustments when necessary. Should you need support with your application due to a disability or long-term condition, feel free to get in touch with us by email headoffice_careers@next.co.uk (please include 'Workplace Adjustments' in the subject line), or call us on 0116 284 2486 and leave a voicemail.
Lead Data Scientist in Leicester employer: Next
Contact Detail:
Next Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Scientist in Leicester
✨Tip Number 1
Network like a pro! Reach out to current employees at NEXT on LinkedIn or through mutual connections. A friendly chat can give you insider info and might just get your foot in the door.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your data science projects, especially those involving machine learning and personalisation. This will help you stand out during interviews.
✨Tip Number 3
Practice makes perfect! Brush up on your SQL and Python skills, and be ready to tackle some technical questions or coding challenges during the interview process.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the NEXT team.
We think you need these skills to ace Lead Data Scientist in Leicester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Lead Data Scientist role. Highlight your experience with machine learning techniques and data analysis, as these are key for us at NEXT. Use specific examples that showcase your skills in SQL, Python, and predictive modelling.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you're passionate about data science and how you can contribute to our eCommerce team. Be sure to mention any leadership experience and how you've successfully guided projects from conception to deployment.
Showcase Your Communication Skills: As a Lead Data Scientist, you'll need to translate complex data insights into actionable strategies. In your application, demonstrate your ability to communicate effectively. Use clear language and avoid jargon where possible to show us you can engage with stakeholders.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. This way, we can ensure your application gets the attention it deserves. Plus, it’s easier for us to keep track of everything!
How to prepare for a job interview at Next
✨Know Your Data Science Stuff
Make sure you brush up on your knowledge of machine learning techniques, especially in PyTorch and TensorFlow. Be ready to discuss specific projects where you've built predictive models or worked with personalisation systems. This will show that you’re not just familiar with the theory but have practical experience too.
✨Understand the Business
Familiarise yourself with NEXT's eCommerce strategies and how data science plays a role in improving customer experience and profitability. Think about how your skills can directly impact their goals and be prepared to share ideas on potential improvements during the interview.
✨Prepare for Technical Questions
Expect to face technical questions related to SQL, Python, and distributed processing. Practice coding problems and be ready to explain your thought process. You might even be asked to solve a problem on the spot, so keep your skills sharp!
✨Showcase Your Communication Skills
As a Lead Data Scientist, you'll need to translate complex data insights into actionable strategies. Prepare examples of how you've effectively communicated findings to non-technical stakeholders. This will demonstrate your ability to bridge the gap between data and business decisions.