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- Tasks: Analyse e-commerce data and develop predictive models to drive growth.
- Company: Leading snacks company in Manchester with a focus on innovation.
- Benefits: Flexible hybrid work, comprehensive benefits, and impactful projects.
- Why this job: Make a difference by optimising strategies that reach millions of consumers.
- Qualifications: Master’s degree in STEM and strong skills in Python and machine learning.
- Other info: 12-month contract with opportunities for career advancement.
The predicted salary is between 36000 - 60000 £ per year.
A leading snacks company in Manchester is seeking a Data Scientist to analyze e-commerce and marketing data. You will develop predictive models, assess sales performance, and optimize pricing strategies.
The ideal candidate will hold a Master’s degree in a STEM field with strong skills in Python and machine learning.
This 12-month fixed-term hybrid contract allows for flexible work, impacting millions of consumers. Comprehensive benefits are offered, emphasizing the importance of analytics in decision-making.
Data Scientist - E-commerce Analytics & Growth (12-Month) in Manchester employer: Kellogg
Contact Detail:
Kellogg Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - E-commerce Analytics & Growth (12-Month) in Manchester
✨Tip Number 1
Network like a pro! Reach out to professionals in the e-commerce and data science fields on LinkedIn. Join relevant groups and participate in discussions to get your name out there.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your predictive models and any projects you've worked on using Python and machine learning. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on common data science questions and case studies. Practice explaining your thought process clearly, as communication is key in this role.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to stay updated on new roles.
We think you need these skills to ace Data Scientist - E-commerce Analytics & Growth (12-Month) in Manchester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in e-commerce analytics and data science. We want to see how your skills in Python and machine learning can contribute to our team!
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 help optimise pricing strategies and assess sales performance at our company.
Showcase Your Projects: If you've worked on any projects related to predictive modelling or data analysis, don’t hold back! We love seeing real examples of your work that demonstrate your skills and creativity.
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!
How to prepare for a job interview at Kellogg
✨Know Your Data
Make sure you brush up on your knowledge of e-commerce analytics and the specific metrics that drive sales performance. Be ready to discuss how you've used data to inform decisions in past projects, especially using Python and machine learning techniques.
✨Showcase Your Predictive Modelling Skills
Prepare to talk about your experience with developing predictive models. Bring examples of how these models have impacted business outcomes, particularly in pricing strategies or marketing campaigns. This will demonstrate your ability to apply theoretical knowledge in a practical setting.
✨Understand the Company’s Market
Research the snacks industry and the company’s position within it. Familiarise yourself with their products and any recent marketing initiatives. This will help you tailor your answers and show that you're genuinely interested in contributing to their growth.
✨Ask Insightful Questions
Prepare thoughtful questions that reflect your understanding of the role and the company. Inquire about their current analytics challenges or how they envision the impact of data science on their future strategies. This shows your enthusiasm and strategic thinking.
