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- Tasks: Create accurate demand models and forecasts for retail clients using data science techniques.
- 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 the retail industry.
- Qualifications: 2+ years in analytics, strong quantitative skills, and proficiency in Python.
- 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 in London 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 in London
✨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 in London
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 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 our team!
How to prepare for a job interview at Revionics, an Aptos Company
✨Know Your Numbers
Brush up on your quantitative skills before the interview. Be ready to discuss specific data models you've worked on and how they impacted business decisions. This will show your potential employer that you can deliver accurate demand models and forecasts.
✨Showcase Your Python Proficiency
Prepare to demonstrate your Python skills during the interview. You might be asked to solve a problem or explain a project where you used Python for data analysis. Having a couple of examples ready will help you stand out.
✨Visualise Your Success
Since data visualisation is key in this role, bring along some examples of your work. Whether it's dashboards or reports, being able to visually communicate your findings will impress your interviewers and show your ability to make data accessible.
✨Emphasise Collaboration
This position is in a dynamic, collaborative environment, so be prepared to discuss how you've worked with others in the past. Share experiences where teamwork led to successful outcomes, highlighting your ability to contribute positively to a team.
