Senior Data Scientist

2 Months ago • 4-8 Years • Data Analyst

About the job

Job Description

Razer Gold seeks a Senior Data Scientist with experience in AML/CFT, statistical modeling, and machine learning to analyze large datasets, build predictive models, and provide data-driven insights for strategic decision making. Strong analytical skills, data management, and communication are essential.
Must have:
  • Data Science Experience
  • Statistical Modeling
  • Machine Learning
  • Python/R/SQL
Good to have:
  • Big Data Tech
  • Data Visualization
  • Data Analysis Libraries
  • Hadoop/Spark
Perks:
  • Global Mission
  • Gamer-Centric Culture
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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 an experienced data scientist to join our team and fulfil the needs of our gamer customer base.

As Senior Data Scientist in Razer Gold, you will own the overall data science solutions for AML and CFT. You should have a strong analytical background, a passion for deriving insights from data and the ability to turn complex data into actionable business solutions. You will be working very closely with AML/CFT and fraud team, data team and various business stakeholders to perform data analysis, develop predictive models and deliver data-driven insights that drive strategic decision.

Data Analysis and Modeling:

  • Develop and implement statistical models, machine learning algorithms, and predictive analytics to solve complex business problems.
  • Analyze large datasets to identify trends, patterns, and insights that support strategic decision-making.

Data Management:

  • Collect, clean, and preprocess data from various sources to ensure data quality and integrity.
  • Maintain and update databases and data pipelines to support ongoing analysis and reporting.

Collaboration and Communication:

  • Work with stakeholders to understand business requirements and translate them into data science solutions.
  • Present findings and recommendations to non-technical stakeholders through clear and actionable reports and visualizations.

Research and Innovation:

  • Stay updated with the latest trends, technologies, and methodologies in data science and analytics.
  • Propose and experiment with new data science techniques and technologies to enhance the company's analytical capabilities.

Project Management:

  • Manage multiple projects simultaneously, ensuring timely delivery and adherence to project goals and objectives.
  • Document processes, methodologies, and results to ensure reproducibility and knowledge sharing.

Pre-Requisites :

Education:

  • Master’s degree or above in Data Science, Statistics, Computer Science, Mathematics, or a related field.

Experience:

  • Proven experience as a Data Scientist or similar role, with a strong portfolio of data science projects.
  • Experience with statistical analysis and machine learning techniques.

Technical Skills:

  • Proficiency in programming languages such as Python, R, or SQL.
  • Experience with data visualization tools (e.g., Tableau, Power BI) and data analysis libraries (e.g., Pandas, NumPy, Scikit-learn).
  • Familiarity with big data technologies (e.g., Hadoop, Spark) is a plus.

Soft Skills:

  • Strong problem-solving skills and attention to detail.
  • Excellent communication and interpersonal skills, with the ability to present complex data insights to non-technical audiences.
  • Ability to work collaboratively in a fast-paced, team-oriented environment.

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About The Company

Shah Alam, Selangor, Malaysia (On-Site)

Shah Alam, Selangor, Malaysia (On-Site)

Singapore (On-Site)

King Of Prussia, Pennsylvania, United States (On-Site)

Singapore (On-Site)

King Of Prussia, Pennsylvania, United States (On-Site)

Singapore (On-Site)

Tokyo, Japan (On-Site)

Tokyo, Japan (Hybrid)

Singapore (On-Site)

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