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- Tasks: Build and enhance the Recommender System for our core platform.
- Company: Join a dynamic scale-up that's making waves in the tech industry.
- Benefits: Enjoy a hybrid work model with 3 days in the office.
- Why this job: Shape product strategy and mentor future data scientists while working on impactful projects.
- Qualifications: Strong background in Statistics or Computer Science with experience in recommendation engines.
- Other info: Exciting opportunity to work with cutting-edge technology in a collaborative environment.
The predicted salary is between 43200 - 72000 £ per year.
Senior Data Scientist – Recommendation Systems
London x3 days in office
Xcede are delighted to be partnering with a very exciting scale-up. The company is operating on a need-to-know basis right now, so if you want to learn more about this one please get in touch!
Responsibilities
- Help to build the Recommender System that powers the company's core platform.
- Help to define the company's Product strategy through creating impactful tools for customers / members.
- Mentor junior engineering & data science hires.
Requirements
- Strong academic background in a relevant field (Statistics, Computer Science, etc.)
- Years of commercial experience working on and deploying recommendation engines
- Excellent Machine Learning and Deep Learning skills
- Experience of working and deploying at scale
- Knowledge Graph and entity linking experience
- General RecSys experience
If this role interests you and you would like to find out more, please apply here or contact us via niall.wharton@Xcede.com (feel free to include a CV for review).
Senior Data Scientist (Recommender Systems) employer: Xcede
Contact Detail:
Xcede Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist (Recommender Systems)
✨Tip Number 1
Make sure to showcase your experience with recommendation systems in your conversations. Highlight specific projects where you've successfully deployed these systems, as this will resonate well with the hiring team.
✨Tip Number 2
Prepare to discuss your approach to mentoring junior team members. The role emphasizes mentorship, so think of examples where you've guided others and how that contributed to their growth and the team's success.
✨Tip Number 3
Familiarize yourself with the latest trends in machine learning and deep learning, especially as they relate to recommender systems. Being able to discuss cutting-edge techniques will demonstrate your passion and expertise in the field.
✨Tip Number 4
Since the company is a scale-up, be ready to talk about your experience working in fast-paced environments. Share examples of how you've adapted to rapid changes and contributed to scaling projects effectively.
We think you need these skills to ace Senior Data Scientist (Recommender Systems)
Some tips for your application 🫡
Highlight Relevant Experience: Make sure to emphasize your years of commercial experience with recommendation engines. Detail specific projects where you deployed these systems and the impact they had.
Showcase Technical Skills: Clearly outline your expertise in Machine Learning and Deep Learning. Mention any relevant tools or frameworks you have used, especially in the context of building scalable systems.
Academic Background: Include your academic qualifications in fields like Statistics or Computer Science. If you have any notable achievements or research, be sure to mention them as well.
Tailor Your Application: Customize your CV and cover letter to reflect the responsibilities and requirements listed in the job description. Show how your skills align with the company's product strategy and goals.
How to prepare for a job interview at Xcede
✨Showcase Your Technical Skills
Be prepared to discuss your experience with recommendation systems in detail. Highlight specific projects where you deployed machine learning and deep learning techniques, and be ready to explain the challenges you faced and how you overcame them.
✨Demonstrate Your Problem-Solving Abilities
Expect to encounter scenario-based questions that assess your analytical thinking. Practice articulating your thought process when tackling complex problems, especially those related to building and optimizing recommender systems.
✨Highlight Mentorship Experience
Since mentoring junior hires is part of the role, share examples of how you've guided less experienced colleagues in the past. Discuss your approach to mentorship and how it has positively impacted team performance.
✨Align with Company Values
Research the company's mission and values before the interview. Be ready to discuss how your personal and professional goals align with theirs, particularly in terms of creating impactful tools for customers and members.
