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- Tasks: Revolutionise retail with hyper-personalised shopping experiences using advanced machine learning.
- Company: VC-backed startup in Greater London focused on innovation.
- Benefits: Competitive compensation, equity, and a collaborative work environment.
- Why this job: Make a real impact by transforming shopping experiences through data science.
- Qualifications: 3-5 years of data science experience and proficiency in Python.
- Other info: Join a dynamic team and shape the future of retail.
The predicted salary is between 43200 - 72000 £ per year.
A VC-backed startup in Greater London is seeking a Senior Data Scientist to revolutionize retail through hyper-personalized shopping experiences. You will be involved in the complete data science stack, implementing advanced machine learning and data pipelines.
Ideal candidates have 3-5 years of experience in data science and are proficient in Python. The role offers competitive compensation and equity, a collaborative environment, and the chance to create impactful solutions that transform shopping experiences.
Senior Data Scientist — Personalization & Recommender Systems in London employer: algo1
Contact Detail:
algo1 Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist — Personalization & Recommender Systems in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow data enthusiasts. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving machine learning and data pipelines. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the latest trends in personalization and recommender systems. Practice common interview questions and be ready to discuss your past experiences in detail.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Senior Data Scientist — Personalization & Recommender Systems in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with Python and any relevant machine learning projects you've worked on. We want to see how you can bring your expertise to the table!
Tailor Your Application: Don’t just send a generic CV! Customise your application to reflect how your background aligns with our mission of revolutionising retail through hyper-personalised experiences. It’ll make you stand out!
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so avoid jargon and get straight to the point about your achievements and what you can bring to our team.
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!
How to prepare for a job interview at algo1
✨Know Your Data Science Fundamentals
Brush up on your core data science concepts, especially those related to machine learning and recommender systems. Be prepared to discuss your previous projects and how you applied these principles in real-world scenarios.
✨Showcase Your Python Skills
Since proficiency in Python is a must, be ready to demonstrate your coding skills. You might be asked to solve a problem on the spot, so practice common algorithms and data manipulation tasks beforehand.
✨Understand the Company’s Vision
Research the startup's mission and how they aim to revolutionise retail. Tailor your answers to show how your experience aligns with their goals, particularly in creating hyper-personalized shopping experiences.
✨Prepare for Collaborative Scenarios
As the role involves working in a collaborative environment, think of examples where you've successfully worked in teams. Highlight your communication skills and how you’ve contributed to group projects in the past.
