At a Glance
- Tasks: Build and deploy ML models to solve complex retail problems for global brands.
- Company: Join a leading customer data science firm with a focus on innovation.
- Benefits: Flexible working, birthday off, and clear career progression opportunities.
- Other info: Collaborative environment with a focus on diversity and inclusion.
- 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
- You'll be embedded in a high-performing team that works directly with client leadership at some of the world's most recognisable retailers and consumer goods companies.
- 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.
- Access to thriving D&I networks and a challenge-and-learn culture.
Location: London (hybrid) | Permanent
This client hires through hackajob — apply via the platform to be considered. We're committed to an inclusive process: let us know if you need any adjustments, and we'll make it work.
Applied Scientist in London employer: hackajob
Join a pioneering company at the forefront of customer data science, where you'll engage in meaningful work that directly influences iconic global brands. With a strong emphasis on employee growth, you will have access to mentorship opportunities and a clear path towards leadership roles, all within a collaborative and inclusive culture. Enjoy the benefits of flexible working arrangements, a supportive team environment, and the chance to tackle complex challenges using cutting-edge technology in the vibrant city of London.
StudySmarter Expert Advice🤫
We think this is how you could land Applied Scientist in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Prepare for interviews by practising common data science questions and case studies. We recommend simulating real interview scenarios with friends or mentors to boost your confidence and refine your answers.
✨Tip Number 3
Showcase your projects! Create a portfolio that highlights your best work, especially those complex ML models and data applications. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re serious about landing that Senior Applied Data Scientist role.
We think you need these skills to ace Applied Scientist in London
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 engaging and personal!
Showcase Your Problem-Solving Skills:In your application, be sure to include examples of how you've tackled complex problems in the past. Whether it's through statistical modelling or mentoring others, we want to see how you approach challenges and deliver results.
Apply Through Our Website:Remember, we only hire through our platform, so make sure to submit your application there. It’s straightforward, and you’ll be one step closer to joining our amazing team at StudySmarter!
How to prepare for a job interview at hackajob
✨Know Your Data Science Stuff
Make sure you brush up on your statistical modelling and machine learning techniques. Be ready to discuss your experience with Python and SQL, especially in a production environment. They’ll want to know how you’ve built and deployed models, so have some examples ready!
✨Speak Their Language
Since you'll be translating complex findings for non-technical stakeholders, practice explaining your work in simple terms. Think about how you would describe a complex model to a CMO. This will show that you can bridge the gap between technical and non-technical teams.
✨Show Off Your Collaboration Skills
This role involves working closely with client teams, so be prepared to talk about your past experiences collaborating on projects. Highlight any instances where you designed scalable solutions or mentored junior colleagues, as this will demonstrate your ability to work well in a team.
✨Get Familiar with Retail Analytics
If you have any experience in retail analytics or category management, make sure to bring it up! Even if it’s not essential, showing that you understand the context of the industry can set you apart. Research common challenges in assortment, pricing, and promotions to discuss during the interview.
