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For Companies At a Glance
- Tasks: Join our data science team to develop machine learning models and improve business outcomes.
- Company: M&S is a dynamic, inclusive retailer focused on quality and exceptional service.
- Benefits: Enjoy a 20% discount, competitive holidays, bonuses, and wellness support.
- Why this job: Be part of a transformative team using cutting-edge tech to drive real impact.
- Qualifications: Passion for data science, basic Python/SQL skills, and a desire to learn.
- Other info: We value diversity and support all applicants throughout the recruitment process.
The predicted salary is between 28800 - 48000 £ per year.
Summary
We are seeking a passionate Data Scientist to contribute to the delivery of machine learning models and other data science components of digital products that improve business outcomes aligned to business and function strategy. Being creative, curious and proactive, you will be an integral part of our data science team and help drive value to the business through AI. You will play a key role in driving our ambition to create a best-in-class data science team, environment, and culture. We are looking for people to join our community of data experts to drive this transformation, build a modern digital ecosystem using exciting technologies and do the best work of their careers.
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’re 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.
Here are some of the benefits we offer that make working for M&S just that little bit more special…
- After completing your probationary period, you’ll receive 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.
What you’ll do
- Contribute to the delivery of data science work that supports the development of customer or colleague facing products.
- Collaborate with other members in a cross-functional team to execute the technical implementation and productionisation of end-to-end machine learning systems.
- Develop own knowledge in data science through training and in-work opportunities.
- Actively collaborate with colleagues, including those outside data science, to develop solutions that address customer requirements and improve value for the organisation.
- Adopt best practice, embrace improvement opportunities, using feedback to learn and develop new technical and non-technical skills, and share knowledge with team members.
Who you are
- Passionate about data science with a keen interest to grow, learn and develop new skills.
- Foundational programming skills in Python and SQL.
- Foundational knowledge of statistics and machine learning methods.
- Basic understanding of the data science and machine learning product life-cycle including model deployment and monitoring.
- Foundational analysis and data storytelling skills.
Everyone’s welcome
We are ambitious about the future of retail. We’re disrupting, innovating and leading the industry into a more conscientious, inspiring digital era. We’re transforming how we work together and offering our most exciting opportunities yet. Marks & Spencer strives to be an inclusive organisation, trusted and admired by our colleagues, customers and suppliers. Join us and make change happen.
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 don’t hesitate to let us know when completing your application. This information will be picked up by our team, so we can try and put steps in place to help you be at your best through this process.
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Data Scientist employer: Marks & Spencer Plc
Contact Detail:
Marks & Spencer Plc Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Show your passion for data science! During the interview, share specific examples of projects or experiences that highlight your enthusiasm and curiosity in the field. This will help you connect with the team and demonstrate that you're a great fit for their culture.
✨Tip Number 2
Familiarize yourself with the latest trends in machine learning and data science. Being able to discuss recent advancements or technologies during your interview can set you apart and show that you're proactive about your professional development.
✨Tip Number 3
Prepare to discuss how you've collaborated with cross-functional teams in the past. Highlighting your ability to work with others outside of data science will demonstrate that you can contribute effectively to their collaborative environment.
✨Tip Number 4
Be ready to talk about your foundational programming skills in Python and SQL. Consider preparing a small project or example that showcases your technical abilities, as this can provide concrete evidence of your skills and readiness for the role.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Understand the Role: Take the time to thoroughly read the job description. Understand the key responsibilities and required skills for the Data Scientist position, such as foundational programming skills in Python and SQL, and knowledge of machine learning methods.
Tailor Your CV: Customize your CV to highlight relevant experience and skills that align with the job requirements. Emphasize any projects or roles where you contributed to data science work or collaborated in cross-functional teams.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data science and your eagerness to grow and learn. Mention specific examples of how you've used data science to drive business outcomes or improve processes.
Showcase Your Skills: In your application, provide examples of your foundational analysis and data storytelling skills. If possible, include links to any relevant projects or portfolios that demonstrate your capabilities in data science.
How to prepare for a job interview at Marks & Spencer Plc
✨Show Your Passion for Data Science
Make sure to express your enthusiasm for data science during the interview. Share specific examples of projects or experiences that ignited your interest and how you envision contributing to the team.
✨Demonstrate Technical Skills
Be prepared to discuss your foundational programming skills in Python and SQL. You might be asked to solve a problem or explain a concept, so brush up on your technical knowledge and be ready to showcase your abilities.
✨Understand the Business Context
Familiarize yourself with how data science impacts business outcomes. Be ready to discuss how your work can align with the company's goals and improve customer experiences, showing that you understand the bigger picture.
✨Emphasize Collaboration and Learning
Highlight your willingness to collaborate with cross-functional teams and learn from others. Share examples of how you've worked with colleagues outside of data science to develop solutions, as teamwork is crucial in this role.
