Data Science Manager - Personalisation in London

Data Science Manager - Personalisation in London

London Full-Time 60000 - 80000 £ / year (est.) No working from home possible
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At a Glance

  • Tasks: Lead a dynamic Data Science team to enhance online personalisation and customer experiences.
  • Company: Join M&S, a vibrant and inclusive brand dedicated to quality and service.
  • Benefits: Enjoy a 20% discount, competitive holidays, bonuses, and extensive wellbeing support.
  • Other info: Embrace a culture of learning and collaboration while driving real change.
  • Why this job: Shape the future of online shopping with innovative ML/AI solutions that truly impact customers.
  • Qualifications: Proven leadership in Data Science and expertise in ML/AI methods.

The predicted salary is between 60000 - 80000 £ per year.

A collaborative and supportive leader who inspires and develops Data Scientists, creating a culture of openness, learning and excellence in delivery. Technically skilled in a wide range of ML/AI methods, with experience turning advanced models into real-world solutions that customers feel and business teams value. You have a pragmatic and commercial mindset, ready and willing to consider the full range of technical options available from simple to complex, depending on what’s most appropriate and will deliver value most effectively. Curious and innovative, keeping pace with new ML/AI advancements and applying them to unlock new ways of serving customers. An excellent communicator and business partner who can make complex concepts simple, building trust and influence with both technical and commercial partners.

What you will do:

  • Lead, manage and grow a high‑performing Data Science team shaping the future of our online Personalisation programme through seamless model‑driven customer experiences.
  • Deliver scalable ML/AI solutions end‑to‑end that step‑change how we understand our customers’ shopping intent and deliver personalised online experiences so that customers can easily find what they are looking for and are inspired by new suggestions.
  • Partner with product, engineering and commercial teams to embed solutions seamlessly into the customer experience and business processes.
  • Set the standard for agile Data Science delivery, testing and model monitoring, ensuring solutions are robust, reliable and impactful.
  • Drive innovation and act as a trusted advisor, helping transform how Data Science creates value for our customers and our business.

What's in it for you:

  • Being a part of M&S is exactly that – playing your part to bring the magic of M&S to our customers every day. We are an inclusive, dynamic, exciting, and ever‑evolving business built on doing the right thing and bringing exceptional quality, value, service to every customer, whenever, wherever and however they want to shop with us.
  • After completing your probationary period, you’ll receive a 20% colleague discount across all M&S products and many of our third‑party brands for you and a member of your household.
  • Competitive holiday entitlement with the potential to buy extra holiday days.
  • Discretionary bonus schemes awarded based on how you achieve your personal objectives and our performance as a business.
  • A generous Defined Contribution Pension Scheme and Life Assurance.
  • A dedicated welcome to our teams with a tailored induction and a wide range of training programmes to develop your skills.
  • Amazing perks and discounts via our M&S Choices portal to maximise your financial and personal wellbeing.
  • Industry‑leading parental, adoption and neonatal policies, providing support and flexibility for your family.
  • Access to a fantastic range of wellbeing support for all colleagues including access to our 24/7 Virtual GP and PAM Assist to support you and your family.
  • A charity volunteer day to support a charity or cause you’re passionate about through a dedicated day away from work.

Our Commitment to Diversity:

We are committed to building diverse and representative teams, where everyone can bring their whole selves to work and be at their best. We support each other and work together to win together. If you feel you’d benefit from any support or reasonable adjustments during any stage of the recruitment process, please let us know when completing your application.

Data Science Manager - Personalisation in London employer: MARKS&SPENCER

Joining M&S as a Data Science Manager means becoming part of a vibrant and inclusive culture that values collaboration, innovation, and excellence. With a strong focus on employee development, you will have access to tailored training programmes and generous benefits, including a 20% discount on products, competitive holiday entitlement, and industry-leading parental policies. M&S is dedicated to creating a supportive environment where your contributions directly enhance customer experiences and drive business success.

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Contact Details:

MARKS&SPENCER Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Data Science Manager - Personalisation in London

Tip Number 1

Network like a pro! Reach out to current employees at M&S 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

Prepare for the interview by practising common questions related to Data Science and personalisation. Think about how you can showcase your leadership skills and technical expertise in real-world scenarios.

Tip Number 3

Showcase your passion for innovation! Be ready to discuss recent ML/AI advancements and how they could be applied to enhance customer experiences at M&S. This will demonstrate your curiosity and forward-thinking mindset.

Tip Number 4

Don’t forget to 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 being part of the M&S team.

We think you need these skills to ace Data Science Manager - Personalisation in London

Leadership
Data Science
Machine Learning
Artificial Intelligence
Model Development
Commercial Mindset
Agile Methodologies

Some tips for your application 🫡

Show Your Leadership Style:As a Data Science Manager, we want to see how you inspire and develop your team. Share examples of how you've created a culture of openness and learning in your previous roles. This will help us understand your collaborative approach!

Highlight Technical Skills:Make sure to showcase your technical prowess in ML/AI methods. We’re looking for someone who can turn complex models into real-world solutions, so don’t hold back on detailing your experience with various techniques and tools.

Communicate Clearly:We value excellent communication skills, so keep your application clear and concise. Use simple language to explain complex concepts, as this reflects your ability to build trust with both technical and commercial partners.

Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity to shape our Personalisation programme!

How to prepare for a job interview at MARKS&SPENCER

Know Your ML/AI Stuff

Brush up on your knowledge of various ML and AI methods. Be ready to discuss how you've applied these techniques in real-world scenarios, especially in personalisation projects. This will show that you can turn complex models into practical solutions.

Showcase Your Leadership Style

Prepare examples that highlight your collaborative leadership approach. Think about times when you've inspired your team or fostered a culture of learning and excellence. This will demonstrate your ability to lead a high-performing Data Science team.

Communicate Complex Ideas Simply

Practice explaining intricate data science concepts in layman's terms. This is crucial for building trust with both technical and commercial partners. Use relatable examples to illustrate your points during the interview.

Be Ready to Innovate

Stay updated on the latest advancements in ML and AI. Be prepared to discuss how you would apply new technologies to enhance customer experiences. Showing curiosity and a willingness to innovate will set you apart as a candidate.