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- Tasks: Create advanced models to predict commodity prices and influence procurement decisions.
- Company: Leading AI firm in London with a focus on innovation.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Join a pioneering team and make a real impact in the world of data science.
- Qualifications: Experience in data science, forecasting, and time series modelling required.
- Other info: Dynamic work environment with a focus on collaboration and creativity.
The predicted salary is between 43200 - 72000 £ per year.
A pioneering AI firm in London is looking for a Data Scientist to develop and implement advanced commodity price prediction models. The candidate should have substantial experience in data science, particularly in forecasting and time series modelling. This role requires collaboration with engineering teams and involves taking a novel approach to data sourcing and model building, ensuring immediate impact on enterprise procurement decisions. An optimal candidate should be comfortable with ambiguity and capable of working with complex, real-world data.
Senior Data Scientist — Enterprise Price Forecasting employer: Monq
Contact Detail:
Monq Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist — Enterprise Price Forecasting
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those already working in data science or at companies you're eyeing. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your forecasting models and time series analyses. When you get the chance to chat with potential employers, having tangible examples of your work can really set you apart.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss how you've tackled ambiguity in past projects. We want to see how you think and approach complex data challenges.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Senior Data Scientist — Enterprise Price Forecasting
Some tips for your application 🫡
Show Off Your Experience: When you’re writing your application, make sure to highlight your substantial experience in data science. We want to see how you've tackled forecasting and time series modelling in the past, so don’t hold back on those details!
Collaboration is Key: Since this role involves working closely with engineering teams, it’s important to mention any collaborative projects you've been part of. We love seeing how you’ve worked with others to achieve great results, so share those stories!
Embrace the Ambiguity: We’re looking for someone who’s comfortable with ambiguity, so don’t shy away from discussing challenges you’ve faced in complex data situations. Show us how you navigated through uncertainty and came out on top!
Apply Through Our Website: Finally, make sure to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Monq
✨Know Your Data Science Stuff
Make sure you brush up on your data science fundamentals, especially around forecasting and time series modelling. Be ready to discuss specific projects where you've successfully implemented these techniques, as this will show your practical experience.
✨Show Off Your Collaboration Skills
Since this role involves working closely with engineering teams, be prepared to share examples of how you've collaborated in the past. Highlight any cross-functional projects you've been part of and how you navigated challenges together.
✨Embrace Ambiguity
The job description mentions comfort with ambiguity, so think of instances where you've thrived in uncertain situations. Discuss how you approached complex problems and what strategies you used to find clarity and solutions.
✨Prepare for Real-World Scenarios
Expect questions that test your ability to work with complex, real-world data. Consider preparing a case study or two from your previous work where you tackled messy datasets and turned them into actionable insights, as this will demonstrate your hands-on expertise.