At a Glance
- Tasks: Develop deep learning models for dating and content segmentation in a collaborative environment.
- Company: Join a forward-thinking company focused on data-driven solutions.
- Benefits: Competitive salary, professional growth, and the chance to work with big data.
- Other info: Exciting opportunities for career advancement and innovation.
- Why this job: Make a real impact by owning projects from research to production.
- Qualifications: Master’s degree and 3 years of experience in deep learning required.
The predicted salary is between 60000 - 80000 £ per year.
As a Data Scientist, you will work in a highly collaborative environment with extensive amounts of data to research and develop deep learning models in the domains of dating, moderation and content segmentation and apply them to tasks such as recommendation systems and analytics at a high scale. You will have a chance to grow and develop professionally by owning data‑driven projects from the research phase through to production, collaborating with highly experienced researchers.
Responsibilities
- Develop classical machine learning and deep learning models that will impact company goals directly.
- Work with partner teams to design and implement solutions in recommender systems, classification and prediction for given objectives.
- Find solutions to complex problems in social network recommendations, understand the data generation process and the challenges involved with working with big data.
- Analyze and leverage the extensive data received from our application to enhance model performance and accuracy.
Qualifications
- Master’s degree in Statistics, Mathematics or Computer Science.
- Minimum of 3 years of experience in designing, developing and deploying production-level deep learning recommendation models with a proven business impact.
- Fluency in Python, Pandas/Dask, SQL, PyTorch or Tensorflow.
- Ability to write readable and maintainable code.
- Strong communication and storytelling skills, capable of presenting complex technical subjects clearly to both technical and non‑technical audiences.
- A proven ability to read and understand AI research publications and implement algorithms and architectures from scratch.
- Ability to effectively integrate and utilize AI tools to optimize workflow efficiency.
Advantages
- Advanced knowledge in generative models: Auto-encoding, adversarial models, compression.
- Experience in developing deep learning graph model solutions.
- Experience with managing and utilizing datasets at the scale of 10s of TB.
- Publication in peer-reviewed conferences or journals on reinforcement learning, deep learning, and machine learning.
- Strong passion for machine learning and investing independent time towards learning, researching, and experimenting with new innovations.
- Strong business acumen or prior industry experience within the social media or messaging space.
Data Scientist employer: Rakuten Viber
Join a forward-thinking company that values innovation and collaboration, where as a Data Scientist, you will have the opportunity to work with extensive datasets in a dynamic environment. Our culture fosters professional growth through ownership of impactful projects and collaboration with seasoned researchers, ensuring that your contributions directly influence our goals. Located in a vibrant area, we offer a supportive atmosphere that encourages continuous learning and experimentation, making it an ideal place for passionate individuals looking to make a difference in the tech landscape.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups or webinars, 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 deep learning models or recommendation systems. This will give potential employers a taste of what you can do and how you tackle complex problems.
✨Tip Number 3
Prepare for interviews by brushing up on your storytelling skills. Be ready to explain your past projects and the impact they had. Remember, it’s not just about the technical stuff; being able to communicate your ideas clearly is key!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented Data Scientists like you. Keep an eye on our job listings and make sure your application stands out by tailoring it to the role.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Scientist role. Highlight your experience with deep learning models and any relevant projects you've worked on. We want to see how your skills align with our needs!
Showcase Your Projects:Include specific examples of data-driven projects you've owned from start to finish. We love seeing how you've tackled complex problems, especially in recommendation systems or analytics. Let us know what impact your work had!
Keep It Clear and Concise:When writing your application, clarity is key! Use straightforward language to explain your technical skills and experiences. Remember, we want to understand your journey without getting lost in jargon.
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 the role. Plus, it shows you're keen on joining our team!
How to prepare for a job interview at Rakuten Viber
✨Know Your Models Inside Out
Make sure you can discuss the deep learning and classical machine learning models you've worked on in detail. Be ready to explain how they were developed, the challenges you faced, and the impact they had on previous projects. This shows your expertise and ability to apply your knowledge practically.
✨Showcase Your Collaboration Skills
Since the role involves working in a highly collaborative environment, prepare examples of how you've successfully collaborated with cross-functional teams. Highlight any specific projects where teamwork led to innovative solutions, especially in recommendation systems or analytics.
✨Prepare for Technical Questions
Brush up on your Python, SQL, and frameworks like PyTorch or TensorFlow. Expect technical questions that test your coding skills and understanding of algorithms. Practising coding problems and reviewing AI research papers can give you an edge in demonstrating your technical prowess.
✨Communicate Clearly and Confidently
You’ll need to present complex ideas to both technical and non-technical audiences. Practice explaining your past projects and technical concepts in simple terms. This will not only showcase your communication skills but also your ability to make data-driven insights accessible to everyone.
