Data Scientist - Fraud Automation Team jobs at Paypal in Ireland, Dublin

Essential Responsibilities:

• Lead the development and implementation of advanced data science models.
• Collaborate with stakeholders to understand requirements.
• Drive best practices in data science.
• Ensure data quality and integrity in all processes.
• Mentor and guide junior data scientists.
• Stay updated with the latest trends in data science.

Minimum Qualifications:

• Minimum of 5 years of relevant work experience and a Bachelor's degree or equivalent experience.

Preferred Qualification:

• 5+ years of experience in data science or machine learning, with at least 2 years applying AI/ML to operations, risk, or fraud 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.
• Familiarity with MLOps tools and concepts (e.g., model serving, observability, retraining).
• Excellent communication skills and a collaborative mindset.
• 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

Essential Responsibilities:

• Lead the development and implementation of advanced data science models.
• Collaborate with stakeholders to understand requirements.
• Drive best practices in data science.
• Ensure data quality and integrity in all processes.
• Mentor and guide junior data scientists.
• Stay updated with the latest trends in data science.

Expected Qualifications:

• Minimum of 5 years of relevant work experience and a Bachelor's degree or equivalent experience.

Your Day-to-Day

• Lead data science initiatives that improve sanctions screening algorithms and optimize detection sensitivity.

• Design and implement data-driven solutions that balance detection precision and false positive reduction.

• Collaborate with advisory, product, and engineering teams to design frameworks supporting sanctions compliance.

• Translate regulatory requirements into actionable analytical frameworks and technical solutions.

• Modernize screening platforms using big data and ML-driven approaches to increase scalability and speed.

• Conduct advanced analytics and identify workflow inefficiencies, recommending actionable improvements.

• Collaborate with engineering teams to ensure deployment, monitoring, and continuous improvement in production systems.

What You Need to Bring

• Bachelor’s degree with a minimum of six years of experience in sanctions transaction screening, profile screening, or AML, including at least three years in data analytics or data science.

• Strong understanding of economic sanctions programs administered by OFAC, EU, UN, CSSF , etc., and associated adjacency risk.

• Proficiency in SQL, BigQuery, Python, R, Tableau, and Power BI, with strong analytical and problem-solving skills.

• Working knowledge of Hadoop, Hive, Jupyter Notebooks, and data warehouse technologies.

• Excellent written and verbal communication skills, with the ability to translate analytical insights into actionable business recommendations.

• Proven ability to manage multiple projects in a fast-paced, dynamic environment with independence and initiative.

Preferred

• Advanced degree in Data Science, Statistics, or a related field.

• Experience deploying and maintaining ML models in production within compliance or regulated environments.

• Familiarity with explainable AI, model validation, and governance frameworks.

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:

• Lead and manage data science projects, ensuring timely delivery and alignment with business goals.
• Develop and maintain data models, algorithms, and reporting systems to support data analysis and decision-making.
• Analyze complex datasets to identify trends, patterns, and insights that drive strategic initiatives.
• Collaborate with cross-functional teams to understand data needs and provide actionable insights.
• Ensure data quality and integrity through regular audits and validation processes.
• Mentor and guide junior data scientists, fostering a culture of continuous learning and improvement.

Expected Qualifications:

• 5+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.

Our Benefits:

Any general requests for consideration of your skills, please

Essential Responsibilities:

• Lead the development and implementation of advanced data science models.
• Collaborate with stakeholders to understand requirements.
• Drive best practices in data science.
• Ensure data quality and integrity in all processes.
• Mentor and guide junior data scientists.
• Stay updated with the latest trends in data science.

Expected Qualifications:

• 3+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.

Our Benefits:

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.

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

Essential Responsibilities:

• Lead complex data science projects, ensuring they meet business objectives and deliver actionable insights.
• Develop advanced data models and algorithms to analyze large datasets and solve complex business problems.
• Collaborate with senior leadership to identify data-driven opportunities for business growth and efficiency.
• Implement best practices for data management, analysis, and visualization.
• Ensure data governance and compliance with relevant regulations and standards.
• Provide mentorship and technical guidance to the data science team.

Expected Qualifications:

• 8+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.
• Experience leading others

Our Benefits:

Any general requests for consideration of your skills, please