At a Glance
- Tasks: Build and deploy ML models to solve complex retail problems for global brands.
- Company: Join a leading customer data science company with a collaborative culture.
- Benefits: Flexible working, birthday off, and clear career progression opportunities.
- Other info: Mentorship opportunities and a dynamic team environment await you.
- Why this job: Make a real impact on iconic brands while working with cutting-edge technology.
- Qualifications: Degree in a quantitative field and strong skills in Python and SQL.
The predicted salary is between 60000 - 80000 £ per year.
hackajob is partnering with a global leader in the customer data science industry to find a Senior Applied Data Scientist for their Advanced Data Science team. This is a rare opportunity to work at the intersection of world-first science and real retail impact, solving some of the most complex category management problems in the industry for iconic global brands.
What you'll be doing
- Build and deploy complex ML models and data science applications end-to-end
- Solve challenging category management problems — assortment, pricing, promotions — using cutting-edge techniques
- Translate analytical findings into clear, actionable insights for non-technical senior stakeholders
- Collaborate with client teams to design scalable, reusable solutions that deliver measurable value
- Mentor junior colleagues and help shape the team's technical standards
What we're looking for
- Essential:
- Degree in Statistics, Mathematics, Physics, Economics, or a related quantitative field
- Production-quality Python and strong SQL — OOP, testing, packaging experience
- Solid statistical modelling across regression, classification, and time-series
- Version control fluency: Git, feature branches, PRs, code reviews
- The ability to explain a complex model to a CMO — you adapt depth to the audience
- Highly advantageous:
- PySpark and distributed data processing at scale
- Nice to have:
- Exposure to retail analytics or category management (assortment, pricing, promotions)
- Experience leading a project workstream or mentoring junior data scientists
Why this role
- Work on problems that directly shape how iconic global brands respond to their customers
- Tesco-scale data infrastructure — PySpark is standard, modern cloud stack throughout
- ~30–40% client-facing: you'll build real relationships with senior commercial leaders
- Clear path to Principal / Lead Data Scientist, with a people management track available
- Flexible working, birthday off, and a genuine small-team feel inside a global company
Applied Scientist employer: hackajob
Join a dynamic and innovative team as a Senior Applied Data Scientist in London, where you'll tackle complex challenges for iconic global brands while enjoying a supportive work culture that prioritises employee growth and collaboration. With access to cutting-edge technology and a clear path for career advancement, including opportunities for mentorship and leadership roles, this company offers a unique environment that fosters both personal and professional development. Enjoy flexible working arrangements and a close-knit team atmosphere within a globally recognised leader in customer data science.
StudySmarter Expert Advice🤫
We think this is how you could land Applied Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those who work at companies you're interested in. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Prepare for interviews by practising your storytelling skills. You want to showcase your experience with ML models and data science applications in a way that resonates with non-technical stakeholders. Make it relatable!
✨Tip Number 3
Don’t just apply anywhere; focus on roles that excite you! Use our platform to find positions that match your skills and interests. Tailor your approach to each opportunity to stand out from the crowd.
✨Tip Number 4
Follow up after interviews! A quick thank-you note can leave a lasting impression. It shows your enthusiasm for the role and keeps you fresh in their minds as they make decisions.
We think you need these skills to ace Applied Scientist
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of Senior Applied Data Scientist. Highlight your experience with ML models, Python, and SQL, and don’t forget to mention any relevant projects that showcase your skills in category management.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and how your background aligns with the challenges mentioned in the job description. Keep it concise but impactful!
Showcase Your Problem-Solving Skills:In your application, be sure to include examples of how you've tackled complex problems in the past. This could be through specific projects or experiences where you’ve used data to drive decisions—make it relatable to retail analytics if possible!
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’re considered for this exciting opportunity. Plus, it makes the process smoother for everyone involved!
How to prepare for a job interview at hackajob
✨Know Your Data Science Stuff
Make sure you brush up on your machine learning models and statistical techniques. Be ready to discuss how you've built and deployed models in the past, and be prepared to explain complex concepts in simple terms. This role is all about translating data into actionable insights, so practice explaining your work to someone without a technical background.
✨Showcase Your Collaboration Skills
Since this position involves working closely with client teams, highlight any experience you have in collaborative projects. Think of examples where you’ve worked with non-technical stakeholders or mentored junior colleagues. Demonstrating your ability to communicate effectively and build relationships will set you apart.
✨Get Familiar with Retail Analytics
If you have any experience in retail analytics or category management, make sure to bring it up during the interview. Even if it's not a requirement, showing that you understand the industry can give you an edge. Research common challenges in retail, like pricing strategies or assortment planning, and be ready to discuss how you could tackle these issues.
✨Prepare for Technical Questions
Expect some technical questions around Python, SQL, and version control. Brush up on your coding skills and be ready to solve problems on the spot. Practising coding challenges or discussing your previous projects can help you feel more confident. Remember, they want to see your thought process, so talk through your reasoning as you go.
