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- Tasks: Lead data science initiatives and create impactful business solutions from scratch.
- Company: Join a globally recognised brand with a blank canvas for innovation.
- Benefits: Opportunity for leadership roles and significant financial impact.
- Why this job: Shape the future of data science in a major company and build your own team.
- Qualifications: Fluency in Python and experience solving complex business problems.
- Other info: Excellent data quality with over 10 million verified customer records.
The predicted salary is between 28800 - 48000 £ per year.
Wyatt Partners are engaged to find a Principal Data Scientist for one of the most recognisable brands on the planet. This is an opportunity to have a tangible impact on the company and also make your mark in the way the company approaches data science from a standards and infrastructure perspective.
It's a role of paradoxes to some extent in that for such a recognised global brand, there is a complete blank canvas when it comes to utilising data science for business solutions. Therefore, we are looking for an individual that would thrive in that 'greenfield' environment, charting their own course, with great potential to build a team around them over the next few years.
The data and its quality you will find at the company is excellent, with over 10 million rich, clean and verified customer data records being a highlight, as well as numerous other internal and external data sets.
To illustrate the impact this role can have, it is only 3 steps away in leadership hierarchy from the CEO, which is rare for what is initially an individual contributor role.
Must have experience:- Fluency with Python
- Track record of building models and providing solutions to complex business problems within a customer-focused business – ideally as an employee rather than external consultant
- Experience working on projects around pricing, promotions, customer segmentation
- Supply chain analytics and forecasting, logistical analysis
- Natural Language Processing
This isn’t a role for someone who wants to be part of a large team of Data Scientists or who is looking for lots of direction in terms of the work they are undertaking. The successful candidate will be someone who wants to make Data Science their baby within this very well-known organisation. If successful, the company can offer a leadership role in return as the division grows, and also a very real chance to add multi-millions to the company’s bottom line in a short space of time, given the quality of data at your disposal.
Principal Data Scientist in London employer: Wyatt Partners
Contact Detail:
Wyatt Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal Data Scientist in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those who work at the company you're eyeing. A friendly chat can give you insider info and might even lead to a referral.
✨Tip Number 2
Show off your skills! Prepare a portfolio or case studies that highlight your experience with Python and data science projects. This will help you stand out during interviews and showcase your problem-solving abilities.
✨Tip Number 3
Be ready to discuss your vision! Since this role is all about charting your own course, think about how you would approach building a data science team and what strategies you'd implement to leverage the company's data.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive and engaged with our platform.
We think you need these skills to ace Principal Data Scientist in London
Some tips for your application 🫡
Show Your Passion for Data Science: Let us see your enthusiasm for data science shine through in your application. Share specific examples of how you've tackled complex business problems using data, especially in customer-focused environments. This is your chance to show that you’re not just a number cruncher but someone who truly loves what they do!
Tailor Your CV and Cover Letter: Make sure your CV and cover letter are tailored to the Principal Data Scientist role. Highlight your experience with Python and any relevant projects you've worked on, particularly those involving pricing, promotions, or customer segmentation. We want to see how your skills align with our needs!
Emphasise Your Independence: Since this role is all about charting your own course, it’s important to highlight your ability to work independently. Share instances where you’ve thrived in a 'greenfield' environment and how you’ve taken initiative to drive projects forward without much direction.
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. Plus, it shows us you’re serious about joining our team!
How to prepare for a job interview at Wyatt Partners
✨Know Your Data Science Stuff
Make sure you brush up on your Python skills and be ready to discuss your experience with building models. Be prepared to share specific examples of how you've solved complex business problems, especially in customer-focused environments.
✨Embrace the Greenfield Opportunity
This role is all about charting your own course, so think about how you can leverage the existing data to create innovative solutions. Come to the interview with ideas on how you would approach this blank canvas and what strategies you would implement.
✨Show Your Leadership Potential
Even though this is initially an individual contributor role, the company is looking for someone who can grow into a leadership position. Highlight any past experiences where you've led projects or teams, and express your enthusiasm for building a team around you in the future.
✨Prepare for the Big Picture
Understand the company's overall goals and how data science can contribute to them. Be ready to discuss how your work can add value to the bottom line and align with the company's vision, especially in areas like pricing, promotions, and customer segmentation.
