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Razer

Senior Data Scientist

Razer is hiring a Senior Data Scientist in Singapore, Singapore. Level rates it ; you can apply on Razer.

Level's read on this job

  • On Level's scale, this data scientist role is Builds AI ●●●●: the job is building AI systems.
  • Tools and skills the posting cites include PyTorch, TensorFlow and RAG.
  • Level classifies it as a senior role.
  • Level lists 148 other open roles at Razer.

AI in this role

pytorchtensorflow
ragai-agents

Joining Razer will place you on a global mission to revolutionize the way the world games. Razer is a place to do great work, offering you the opportunity to make an impact globally while working across a global team located across 5 continents. Razer is also a great place to work, providing you the unique, gamer-centric #LifeAtRazer experience that will put you in an accelerated growth, both personally and professionally.

Job Responsibilities :

Razer Gold aims to become the world’s leading payment service provider for games and digital content. As our business grows to meet the needs of gamers globally, we are looking for a Senior Data Scientist to join our team and fulfill the needs of our gamer customer base by AI technologies.

This Senior Data Scientist in Razer Gold role will focus on designing and developing advanced AIML/GenAI solution and play a key role in the Razer Gold Data Scientist team. The ideal candidate will have strong expertise in machine learning, deep learning, LLM fine-tune, Generative AI agents, and Retrieval-Augmented Generation (RAG). This role involves working closely with AI engineers, data engineers, and product managers and various business stakeholders to build advanced AIML/GenAI solutions .

This Senior Data Scientist in Razer Gold role will focus on designing and developing advanced AIML/GenAI solution and play a key role in the Razer Gold Data Scientist team. The ideal candidate will have strong expertise in machine learning, deep learning, LLM fine-tune, Generative AI agents, and Retrieval-Augmented Generation (RAG). This role involves working closely with AI engineers, data engineers, and product managers and various business stakeholders to build advanced AIML/GenAI solutions .

 

Job responsibilities

  • Translate business needs/problems into well-defined AIML/GenAI solution designs.

  • Develop AIML/GenAI solutions, including data preparation, model training, optimization and evaluation.

  • Apply latest GenAI related technologies and aim at intelligent process automation and efficiency gains for Razer Gold business.

  • Collaborate with engineering teams to build robust AI solutions pipeline and deploy AIML/GenAI solutions.

  • Participate in the design, development and implementation of Razer Gold AI-powered products/solutions/platform.

  • Communicate complex data findings/insights by AI-driven solutions to business leaders and technical teams.

  • Relevant exposure to fraud and financial crimes compliance AI initiatives would be preferred."

 

Technical Skills

  • Proficiency in programming languages commonly used in data science such as Python, SQL.

  • Proficiency in Python and experience with PyTorch or TensorFlow for deep learning.

  • Solid knowledge of machine learning/deep learning and Generative AI.

  • Familiar with AIML/GenAI frameworks.

  • Experience of prompting engineering, LLM fine-tune/evaluation, RAG system, Agentic AI, MCP and reinforcement learning.

  • Experience with cloud data platforms and cloud-based AI deployment (AWS, GCP, or Azure).

  • Experience with big data technologies like Spark, Hadoop, or distributed computing frameworks.

  • Experience of handling large-scale structured and unstructured data.

 

Education background & Experience:

  • Master's or PHD degree in Computer Science, Artificial Intelligence, Data Science, Machine learning or related Fields.

  • 2+ years of working experience in GenAI/AIML learning domain.

  • Working experience in fintech, payments, or fraud detection domain is a plus.

  • Strong problem-solving skills and communication skills, with the ability to work cross-functionally and influence stakeholders.

Pre-Requisites :

Razer is proud to be an Equal Opportunity Employer. We believe that diverse teams drive better ideas, better products, and a stronger culture. We are committed to providing an inclusive, respectful, and fair workplace for every employee across all the countries we operate in. We do not discriminate on the basis of race, ethnicity, colour, nationality, ancestry, religion, age, sex, sexual orientation, gender identity or expression, disability, marital status, or any other characteristic protected under local laws. Where needed, we provide reasonable accommodations - including for disability or religious practices - to ensure every team member can perform and contribute at their best.

Are you game?

How we rate this

Senior Data Scientist at Razer rates 98 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGAI agentsPyTorchTensorFlow

Also common in data scientist jobs at this level

Pay

Typical data scientist job
$167k

This posting doesn't list pay. Use the typical data scientist figure when pay comes up. See data scientist jobs

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. How do you decide when an AI agent can act on its own versus asking for approval first?
  3. What are the limits of PyTorch that you've run into, and how did you work around them?
  4. What's a project where you used TensorFlow hands-on?
  5. How would you decide a model or AI system is ready to ship?

Adapt your resume

  • List these exact terms on your resume: RAG, AI agents, PyTorch, and TensorFlow. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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