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- Tasks: Create accurate demand models and forecasts for retail clients using data science.
- Company: Leading provider of innovative retail pricing solutions.
- Benefits: Competitive rewards, remote work flexibility, and a dynamic team environment.
- Why this job: Join a collaborative team and make a real impact in retail analytics.
- Qualifications: 2+ years in analytics, strong quantitative skills, and Python proficiency.
- Other info: Exciting opportunities for growth in a fast-paced industry.
The predicted salary is between 36000 - 60000 £ per year.
A leading provider of retail pricing solutions is looking for an Applied Data Scientist. This role, based in London or remotely across the UK, involves delivering accurate demand models and forecasts to retail customers.
The ideal candidate will have:
- Strong quantitative skills
- At least 2 years of experience in analytics
- Proficiency in Python and data visualization tools
The position offers competitive rewards and the chance to work in a dynamic, collaborative environment.
Remote Data Scientist – Retail Forecasting & Pricing employer: Revionics, an Aptos Company
Contact Detail:
Revionics, an Aptos Company Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Remote Data Scientist – Retail Forecasting & Pricing
✨Tip Number 1
Network like a pro! Reach out to people in the retail and data science sectors on LinkedIn. A friendly message can go a long way, and you never know who might have the inside scoop on job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data visualisation projects and demand models. This is your chance to demonstrate your expertise in Python and analytics, making you stand out to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on common data science questions and case studies. Practising with friends or using mock interview platforms can help us feel more confident and ready to impress.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of exciting opportunities, and applying directly can sometimes give you an edge. Plus, it’s super easy to keep track of your applications!
We think you need these skills to ace Remote Data Scientist – Retail Forecasting & Pricing
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your quantitative skills and experience in analytics. We want to see how your background aligns with the role of a Data Scientist in retail forecasting and pricing.
Showcase Your Skills: Don’t forget to mention your proficiency in Python and any data visualisation tools you’ve used. We love seeing practical examples of how you've applied these skills in your previous roles.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about retail forecasting and pricing. Share specific experiences that demonstrate your ability to deliver accurate demand models and forecasts.
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 don’t miss out on any important updates from us!
How to prepare for a job interview at Revionics, an Aptos Company
✨Know Your Data
Make sure you brush up on your quantitative skills and be ready to discuss your experience with data analysis. Be prepared to explain how you've used Python and data visualisation tools in past projects, as this will show your practical knowledge.
✨Understand Retail Forecasting
Familiarise yourself with retail forecasting concepts and methodologies. Being able to discuss how demand models work and their importance in pricing strategies will demonstrate your industry knowledge and make you stand out.
✨Prepare for Technical Questions
Expect technical questions that assess your analytical thinking and problem-solving abilities. Practise coding challenges in Python and be ready to showcase your thought process when tackling data-related problems.
✨Show Your Collaborative Spirit
Since the role involves working in a dynamic, collaborative environment, be prepared to share examples of how you've successfully worked in teams. Highlight your communication skills and how you’ve contributed to group projects in the past.
