דרושים Offensive Fraud Engineer ב-Paypal ב-Ireland, Dublin

Essential Responsibilities:

• Develop and optimize machine learning models for various applications.
• Preprocess and analyze large datasets to extract meaningful insights.
• Deploy ML solutions into production environments using appropriate tools and frameworks.
• Collaborate with cross-functional teams to integrate ML models into products and services.
• Monitor and evaluate the performance of deployed models.

Expected Qualifications:

• 3+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.
• Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
• Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.
• Several years of experience in designing, implementing, and deploying machine learning models.

Our Benefits:

Any general requests for consideration of your skills, please

Technical Execution:

• Plan and execute red team engagements simulating real-world fraud attacks to expose gaps in fraud detection and prevention systems.
• Develop and deploy fraud attack simulations, including account takeover scenarios, synthetic identity fraud, payment manipulation, and automated bot attacks. You will collaborate closely with fraud operations, data science teams, and InfoSec to develop purple team strategies that continuously refine both offensive techniques and defensive capabilities.
• Conduct research on fraudsters' toolkits, malware, and automated fraud tools used against PayPal and its affiliates, analyzing network traffic patterns and behavioral indicators associated with fraud

What You Need to Bring

Required:

• 6+ years of experience in offensive security, cybercrime, cyber-fraud, or related areas
• Demonstrated experience building security capabilities or teams from inception
• Leadership experience coordinating technical activities and influencing cross-functional stakeholders
• Experience conducting red team engagements with fraud-related techniques (account manipulation, payment fraud simulation, data exfiltration)
• Proficiency in attack automation and tool development
• In-depth familiarity with the cybercrime and cyber-fraud environment
• Proficiency in multiple programming languages and both Linux and Windows environments
• Strategic thinking and entrepreneurial mindset

Preferred:

• Published security or fraud research (tools, papers, exploit analysis)
• Experience as a founding member or early hire in security teams
• Knowledge of network protocols, traffic analysis, and fraud detection technologies (SIEM, EDR, anti-fraud engines)
• Experience with big data platforms (Splunk, Hadoop) and machine learning approaches to fraud detection
• Knowledge of payment systems, digital wallets, and e-commerce fraud vectors
• Industry certifications (OSCP, OSCE, GPEN, GXPN)
• Track record of influencing security strategy at the organizational level

Our Benefits:

Any general requests for consideration of your skills, please

Essential Responsibilities:

• Design and implement holistic and data-driven solutions to support Paypal’s global financial and fraud risk objectives.
• Partner with product and platform engineering teams to build cutting-edge, scalable, and secure ML-based products that enhance global customer experiences.
• Collaborate closely with data engineering and analytics teams to ensure reliable, high-quality training data and robust monitoring infrastructure.
• Oversee the development and maintenance of production-level data pipelines, machine learning algorithms, and advanced statistical models.
• Utilize large-scale datasets to perform exploratory data analysis and feature engineering to drive strategic business decisions.
• Ensure data integrity, fairness, and explainability in deployed machine learning systems through rigorous testing, validation, and bias detection practices.
• Communicate business insights and progress updates effectively to stakeholders and senior leadership through clear visualizations and narratives.
• Lead, mentor, and grow a team of data scientists and ML engineers, fostering innovation in machine learning techniques such as supervised learning, unsupervised learning, reinforcement learning, and deep learning.

• 8+ years of work experience in relevant positions (e.g. data scientist, data analyst, statistician, decision scientist, FP&A, product/process manager, risk management, army intelligence units) domains.
• Strong proficiency in Python, SQL, and ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow).
• Experience with LLMs, prompt engineering, RAG pipelines, or AI agents is a strong plus.
• Deep understanding of root cause analysis, anomaly detection, or incident forensics.
• Proven ability to translate business problems into data science solutions.
• Excellent communication skills and a collaborative mindset.
• Quick-thinker, fast learner, wide general knowledge, problem solver
• Bachelor’s or Master’s in Computer Science, Statistics, Engineering, or related field. PhD a plus.

Belonging at PayPal:

Any general requests for consideration of your skills, please

Essential Responsibilities:

• Develop and optimize machine learning models for various applications.
• Preprocess and analyze large datasets to extract meaningful insights.
• Deploy ML solutions into production environments using appropriate tools and frameworks.
• Collaborate with cross-functional teams to integrate ML models into products and services.
• Monitor and evaluate the performance of deployed models.

Minimum Qualifications:

• Minimum of 5 years of relevant work experience and a Bachelor's degree or equivalent experience.
• Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
• Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.
• Several years of experience in designing, implementing, and deploying machine learning models.

Preferred Qualification:

• MSc or equivalent experience in a quantitative field (Computer Science, Mathematics, Engineering, Artificial Intelligence, etc.) or a bachelor's degree in engineering, science, statistics or mathematics with a strong technical background in machine learning.
• Hands-on experience with Python or Java, along with relevant technologies such as Spark, Hadoop, Big-Query, SQL, is required.
• Candidates must possess a comprehensive understanding of machine learning algorithms and explainable AI techniques. Additionally, expertise in at least one of the following specialized areas is required: Computer Vision, Graph Mining, Natural Language Processing (NLP), or Generative AI (GenAI).
• Experience with Cloud frameworks such as GCP, AWS is preferred.
• Experience withdeveloping machine learning modelsat scale from inception to business impact
• Experience in designing ML pipelines, including model versioning, model deployment, model testing, and monitoring
• Experience in mentoring and supporting junior data scientists or engineers.
• Experience working in a multi-cultural and multi-location organization – an advantage.
• Team player, responsible, delivery-oriented, details-oriented, outstanding communication skills.

Our Benefits:

Any general requests for consideration of your skills, please

Essential Responsibilities:

• Design and implement holistic and data-driven solutions to support Paypal’s global financial and fraud risk objectives.
• Partner with product and platform engineering teams to build cutting-edge, scalable, and secure ML-based products that enhance global customer experiences.
• Collaborate closely with data engineering and analytics teams to ensure reliable, high-quality training data and robust monitoring infrastructure.
• Oversee the development and maintenance of production-level data pipelines, machine learning algorithms, and advanced statistical models.
• Utilize large-scale datasets to perform exploratory data analysis and feature engineering to drive strategic business decisions.
• Ensure data integrity, fairness, and explainability in deployed machine learning systems through rigorous testing, validation, and bias detection practices.
• Communicate business insights and progress updates effectively to stakeholders and senior leadership through clear visualizations and narratives.
• Lead, mentor, and grow a team of data scientists and ML engineers, fostering innovation in machine learning techniques such as supervised learning, unsupervised learning, reinforcement learning, and deep learning.

Preferred Qualification:

• 8+ years of work experience in relevant positions (e.g. data scientist, data analyst, statistician, decision scientist, FP&A, product/process manager, risk management, army intelligence units) domains.
• Strong proficiency in Python, SQL, and ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow).
• Experience with LLMs, prompt engineering, RAG pipelines, or AI agents is a strong plus.
• Deep understanding of root cause analysis, anomaly detection, or incident forensics.
• Proven ability to translate business problems into data science solutions.
• Excellent communication skills and a collaborative mindset.
• Quick-thinker, fast learner, wide general knowledge, problem solver
• Bachelor’s or Master’s in Computer Science, Statistics, Engineering, or related field. PhD a plus.

Our Benefits:

Any general requests for consideration of your skills, please

Our Benefits:

Any general requests for consideration of your skills, please

What You’ll Do

• Design and develop internal-facing AI tools that help analysts explore data, generate SQL, detect anomalies, and summarize trends.
• Develop and maintain backend services and APIs to support AI and data workflows
• Query and profile data across multiple sources (BigQuery, logs, etc.) and ensure reliable, fast access for tools.
• Collaborate closely with analysts and stakeholders to deeply understand their workflows and build what matters most.
• Integrate LLMs (e.g., OpenAI, open-source models) for natural language interfaces, auto-insights, or content summarization.
• Build intuitive UIs or work with frontend engineers to create React-based apps.
• Ensure security and compliance with internal access controls, logging, and audit standards.
• Prototype, test, and iterate quickly based on feedback and evolving needs.

Must-Have Skills

• Bachelor’s or Master’s in Computer Science, Statistics, Engineering, or related field; 3+ years of experience in machine learning
• Strong programming skills in Python , with experience using data and ML libraries (pandas, scikit-learn, etc.).
• Proficiency in SQL and data querying from cloud data warehouses. Ensure data quality and integrity in all processes.
• Experience with building backend APIs (FastAPI, Flask) and deploying services.
• Familiarity with LLMs and NLP concepts , and basic prompt engineering.
• Ability to build usable UIs with Streamlit, Dash, or collaborate with frontend teams.
• Strong product sense and empathy for analysts’ workflows and challenges, collaborate with stakeholders to understand requirements.

Nice-to-Have Skills

• Experience in risk or fraud domains big plus
• Experience with LLM applications like Retrieval-Augmented Generation (RAG) or semantic SQL generation.
• Cloud experience (GCP) and containerization (Docker).
• Background in MLOps, data quality monitoring, or internal tooling platforms.
• Experience with tools like Looker, Tableau from a data backend perspective.

Our Benefits:

Any general requests for consideration of your skills, please