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Jobs in Singapore   »   Jobs in Singapore   »   Engineering Job   »   CTM Platform/Data Engineer
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CTM Platform/Data Engineer

Paypal Pte. Ltd.

Job Description Summary:

We are seeking a skilled Cyber Analytics Engineer with a background in Machine Learning to join our Cybersecurity Operations team. This role is pivotal in developing advanced capabilities to support our Threat Detection Engineering, Cyber Defense Center, Cyber Threat Intelligence and Offensive Security teams. The ideal candidate will leverage data analytics and machine learning techniques to create innovative solutions that enable faster detection and automated response to emerging threats. If you are passionate about cybersecurity and have a strong background in data science, this is the opportunity for you to make a significant impact in protecting our organization.

Job Description:

As a member of our Cyber Data Science and Engineering team, this role will work with our Cybersecurity Operations team to identify opportunities to translate our data-at-scale to into actionable outcomes through data science and engineering approaches.

Supporting the following services, an ideal candidate will be able to:

Advanced Threat Detection:

  • Design, develop, and implement machine learning models for detecting and responding to cyber threats across various data sources, including network traffic, user behavior, endpoint activity, and product web sessions.
  • Continuously refine and enhance detection algorithms based on new threat intelligence and feedback from incident response teams.

Threat Intelligence Integration:

  • Analyze and apply threat intelligence data to improve detection capabilities, ensuring that models are trained on the latest threat actor behaviors and techniques.
  • Collaborate with threat intelligence teams to integrate contextual data into services to all stakeholders, enhancing the accuracy and effectiveness of cyber operations.

Automated Response Solutions:

  • Develop automated response systems that leverage machine learning outputs to initiate immediate actions against detected threats, reducing response times and mitigating risks.

Data Collection, Analysis and Visualization:

  • Perform in-depth data analysis to uncover insights and trends related to cybersecurity incidents, leveraging statistical methods and visualization tools.
  • Present findings and actionable recommendations to stakeholders, including technical teams and executive leadership.

Collaboration and Knowledge Sharing:

  • Collaborate with cross-functional teams, including cybersecurity analysts, incident responders, and IT personnel, to ensure alignment on detection strategies and response protocols.
  • Contribute to the development of best practices and documentation related to machine learning and data science applications in cybersecurity.

Skills we think will make you successful in this role include:

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Cybersecurity, or a related field.
  • 3+ years of experience in data science and machine learning, preferably within a cybersecurity context.
  • Proficiency in programming languages such as Python or R, and experience with machine learning frameworks (e.g., MLlib, TensorFlow, PyTorch, Scikit-learn).
  • Familiarity with cybersecurity concepts, threat detection methodologies, and threat intelligence frameworks.
  • Strong analytical skills with the ability to translate complex data into actionable insights.
  • Excellent communication skills, capable of conveying technical concepts to non-technical audiences.
  • Excellent written and verbal technical communication skills, capability of communicating detailed machine learning concepts to other Machine Learning Engineers
  • Experience with data visualization tools (e.g., Tableau, Power BI, Looker).
  • Experience designing new and working with existing deep learning models.
  • Experience with NLP models like embedding models and transformer models.
  • Experience working with time series data.
  • Experience working with supervised, unsupervised, and semi-supervised machine learning settings.
  • Experience developing and testing software services for production deployment.
  • Experience working with data lake technology like Big Query and delta lake.

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