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- Tasks: Develop demand forecasting models and collaborate with Sales and Marketing teams.
- Company: High-growth data-driven business in the UK with a focus on speed and impact.
- Benefits: Ownership of critical models and a dynamic, high-performing team environment.
- Why this job: Make a real business impact while honing your data science skills.
- Qualifications: 1-3 years of experience in forecasting, time-series analysis, Python, and SQL.
- Other info: Join a culture that values collaboration and innovation.
The predicted salary is between 36000 - 60000 £ per year.
A high-growth data-driven business in the UK seeks a Data Scientist to develop demand forecasting models. You will be part of a high-performing team and collaborate with departments including Sales and Marketing.
Ideal candidates have:
- 1-3 years of experience
- Strong skills in forecasting and time-series analysis
- Proficiency in Python and SQL
This role offers real ownership of business-critical models and a culture focused on speed and impact.
Demand Forecasting Scientist — Drive Real Business Impact in London employer: Omnis Partners
Contact Detail:
Omnis Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Demand Forecasting Scientist — Drive Real Business Impact in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those working in demand forecasting or data science. A friendly chat can lead to insider info about job openings and even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your forecasting models and time-series analysis projects. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your Python and SQL skills. Be ready to discuss how you've used these tools in past projects, as well as how you approach problem-solving in demand forecasting.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might be perfect for you. Plus, it’s a great way to show your enthusiasm for joining our high-performing team.
We think you need these skills to ace Demand Forecasting Scientist — Drive Real Business Impact in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with forecasting and time-series analysis in your application. We want to see how your skills in Python and SQL can drive real business impact!
Tailor Your Application: Don’t just send a generic CV! Tailor your application to reflect the specific requirements of the Demand Forecasting Scientist role. We love seeing candidates who take the time to connect their experience with what we’re looking for.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate straightforward communication, so make sure your key achievements and experiences shine through without any fluff!
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 Omnis Partners
✨Know Your Forecasting Models
Make sure you brush up on your demand forecasting models and time-series analysis techniques. Be ready to discuss specific models you've worked with, how they impacted business decisions, and any challenges you faced.
✨Showcase Your Technical Skills
Since proficiency in Python and SQL is key for this role, prepare to demonstrate your coding skills. You might be asked to solve a problem or analyse data on the spot, so practice common tasks and be ready to explain your thought process.
✨Understand the Business Impact
This role is all about driving real business impact, so think about how your work can influence sales and marketing strategies. Be prepared to share examples of how your forecasting has led to tangible results in previous roles.
✨Collaborate and Communicate
As you'll be working closely with various departments, highlight your teamwork and communication skills. Prepare examples of successful collaborations and how you’ve effectively communicated complex data insights to non-technical stakeholders.
