Senior Data Scientist - Recommendations

Viber
City of London
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist (GenAI)

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

This job is brought to you by Jobs/Redefined, the UK's leading over-50s age inclusive jobs board.

Description

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.

Responsibilities

  1. Work with management and partner teams to design and implement solutions in recommender systems for given objectives.
  2. Lead technical efforts to improve the performance of deep learning models and propose initiatives to impact company goals directly.
  3. Autonomously find solutions to complex problems in social network recommendations and understand the data generation process and challenges with the data.
  4. Analyze and leverage the extensive data received from our application to enhance model performance and accuracy.

Requirements

  1. Master's degree in Statistics, Mathematics or Computer Science.
  2. Minimum of 4 years of experience in designing, developing and deploying production-level deep learning recommendation models with a proven business impact.
  3. Fluency in Python, Pandas/Dask, SQL, PyTorch or Tensorflow. Ability to write readable and maintainable code.
  4. Strong communication and storytelling skills with both technical and non-technical audiences. Ability to present complex technical subjects to non-technical stakeholders.
  5. Ability to read AI research publications and implement the algorithms & architectures from scratch.

Advantages

  1. Advanced knowledge in generative models: Auto-encoding, adversarial models, compression.
  2. Worked on deep learning graph model solutions with 10's of TB of data.
  3. Publication in peer-reviewed conferences or journals on reinforcement learning, deep learning, and machine learning.
  4. Strong passion for machine learning and investing independent time towards learning, researching, and experimenting with new innovations in the field.
  5. Experience working with technologies like SageMaker, Athena/Trino, Spark, Milvus, and OpenSearch.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.