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Senior Data Scientist
Rakuten Viber is one of the most popular and downloaded apps in the world. Working with us provides a unique opportunity to influence hundreds of millions of our users and to be part of the journey that makes us a super-app. Our mission is to make people’s lives easier by enabling meaningful connections, from precious moments with family and friends, through managing business relationships to pursuing their passions. Connecting people across the world is a complex problem with many machine-learning applications. The purpose of this role is to implement mathematical models and algorithms to solve complex business problems in recommendations and classification. Successful outcomes will significantly impact our hundreds of millions of daily active users around the globe. As a Senior 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.
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I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Responsibilities Work with management and partner teams to design and implement solutions in recommender systems for given objectives. Lead technical efforts to improve the performance of deep learning models and propose initiatives to impact company goals directly. Autonomously find solutions to complex problems in social network recommendations and understand the data generation process and challenges with the data. Analyze and leverage the extensive data received from our application to enhance model performance and accuracy.
Requirements Master’s degree in Statistics, Mathematics or Computer Science. Minimum of 4 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 with both technical and non-technical audiences. Ability to present complex technical subjects to non-technical stakeholders. Ability to read AI research publications and implement the algorithms & architectures from scratch.
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Advantages Advanced knowledge in generative models: Auto-encoding, adversarial models, compression. Worked on deep learning graph model solutions with 10’s of TB of data. 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 in the field. Experience working with technologies like SageMaker, Athena/Trino, Spark, Milvus, and OpenSearch.
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