Job Description
As a Lead Data Analyst at Razer, you will drive impactful insights across fraud detection, business performance, user behavior, and product optimization. You will lead analytical projects, collaborate with risk, product, compliance, and marketing stakeholders to shape data-driven decisions. Additionally, you will champion the use of AI and large language models (LLMs) to foster business and operational innovation, contributing to Razer's global mission to revolutionize gaming.
Good To Have:
- Experience in fintech, e-commerce, or digital payments industries.
- Hands-on experience developing or implementing AI/ML or GenAI solutions.
- Experience with cloud data platforms (AWS, GCP, or Azure).
Must Have:
- Lead data analysis projects for fraud detection and business intelligence.
- Define KPIs and deliver actionable insights to stakeholders.
- Build and maintain automated dashboards and reports.
- Support fraud and risk control through data analysis.
- Partner with AI/ML engineers for model development and deployment.
- Collaborate on designing and applying large language models (LLMs).
- Drive data storytelling and visualization.
- Document analytical processes and data definitions.
- Mentor junior analysts and develop analytics best practices.
- Bachelor's or Master’s degree in Statistics, Math, CS, Economics.
- 5+ years experience in data analysis or business intelligence.
- Strong SQL skills.
- Proficiency in Python, R, or other analytical programming languages.
- Experience with Tableau, Power BI, or QuickSight.
- Familiarity with AI/ML frameworks like scikit-learn, TensorFlow, PyTorch.
- Understanding of LLM concepts including embeddings and prompt engineering.
- Experience leveraging AI tools such as ChatGPT, Claude, LangChain.
Perks:
- Global mission to revolutionize gaming.
- Opportunity to make a global impact.
- Work across a global team (5 continents).
- Gamer-centric #LifeAtRazer experience.
- Accelerated personal and professional growth.
- Certified as a Great Place to Work® (US and Singapore).
Job Responsibilities:
As a Lead Data Analyst, you will play a key role in delivering impactful insights across multiple business domains including fraud detection, business performance, user behavior, and product optimization. You will lead analytical projects, partner with stakeholders across risk, product, compliance, and marketing, and help shape data-driven decision-making. You will also help champion the use of AI and large language models (LLMs) in driving business and operational innovation.
Key Responsibilities:
- Lead the development and execution of data analysis projects to support fraud detection, operational monitoring, business intelligence, and performance reporting.
- Work closely with stakeholders to understand business problems, define KPIs, and deliver actionable insights and recommendations.
- Build and maintain automated dashboards and reports that support strategic and operational decision-making across teams.
- Support fraud and risk control initiatives through data analysis of transaction patterns, behavioral signals, and case investigation metrics.
- Partner with AI/ML engineers and data scientists to develop, evaluate, and deploy models that enhance automation and intelligence in business operations.
- Collaborate on the design and application of large language models (LLMs) and other AI tools to solve analytical and operational challenges.
- Drive data storytelling and visualization to clearly communicate trends, risks, and opportunities.
- Document analytical processes, KPIs, and data definitions to maintain high standards of data governance.
- Mentor junior analysts and contribute to the development of best practices in analytics, AI applications, and reporting.
Key Qualifications:
- Bachelor's or Master’s degree in Statistics, Mathematics, Computer Science, Economics, or a related field.
- 5+ years of experience in data analysis or business intelligence, with exposure to risk or fraud analytics considered a plus.
- Strong SQL skills and proficiency in Python, R, or other analytical programming languages.
- Experience with business intelligence tools such as Tableau, Power BI, or QuickSight.
- Familiarity with AI/ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch) and understanding of LLM concepts (e.g., embeddings, prompt engineering).
- Experience leveraging AI tools (e.g., ChatGPT, Claude, LangChain) for data exploration, reporting automation, or business solution development.
- Strong communication and collaboration skills, with experience working cross-functionally.
- Ability to translate complex data findings into clear business insights.
- Organized, detail-oriented, and capable of managing multiple analytical projects.
Nice to Have:
- Experience in fintech, e-commerce, or digital payments industries.
- Hands-on experience developing or implementing AI/ML or GenAI solutions in business environments.
- Experience with cloud data platforms (e.g., AWS, GCP, or Azure).
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