At a Glance
- Tasks: Develop deep learning models for dating, moderation, and content segmentation.
- Company: Join a dynamic team focused on innovative data solutions.
- Benefits: Competitive salary, professional growth, and collaborative work environment.
- Other info: Opportunity to work with big data and cutting-edge AI technologies.
- Why this job: Make a real impact with your data skills in a fast-paced industry.
- Qualifications: Master’s degree and 3 years of experience in deep learning models.
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, 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 and recommendation systems. This will give potential employers a taste of what you can do and how you think.
✨Tip Number 3
Prepare for interviews by brushing up on your storytelling skills. Be ready to explain complex technical concepts in simple terms, as you'll need to communicate effectively with both techies and non-techies alike.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it gives you a chance to showcase your enthusiasm for the role right from the start.
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 and avoid jargon where possible. We appreciate a well-structured application that tells a story about your journey and expertise.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Rakuten Viber
✨Know Your Models Inside Out
Make sure you can discuss the deep learning and 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 helps you connect with the interviewers.
✨Showcase Your Data Skills
Prepare to talk about your experience with big data and the tools you’ve used, like Python, Pandas, and SQL. Bring examples of how you've analysed data to improve model performance. This will demonstrate your hands-on experience and problem-solving abilities.
✨Communicate Clearly
Practice explaining complex technical concepts in simple terms. You might be asked to present your work to non-technical stakeholders, so being able to tell a compelling story about your data findings is crucial. Think of ways to make your explanations relatable.
✨Stay Updated on AI Trends
Familiarise yourself with the latest research and innovations in AI and machine learning. Being able to discuss recent advancements or publications shows your passion for the field and your commitment to continuous learning, which is highly valued in this role.
