דרושים Sr Machine Learning Engineer ב-Paypal ב-Ireland, Dublin

Essential Responsibilities:

• Complete level two quality reviews, efficiently and accurately identifying opportunities within the cases that you review, completing your reviews in a timely manner.
• Apply analytic techniques to complex information sets in order to make logical and supported recommendations to leadership and to your direct reports on cases for reporting to regional regulatory authorities.
• Direct and coach your team to ensure they are successful in the following daily efforts:
• Conducting reviews of potential illegal activity or activity in violation of the regulations or PayPal policies
• Completing a time-sensitive and meticulous analysis of each instance of potential Anti-Money Laundering activity and/or suspicious financial activity across multiple jurisdictions and countries.
• Assessing customer profiles and large amounts of data to ensure normal and expected activity, including Acceptable Use Policy adherence and Know Your Customer efforts.
• Documenting findings in narrative style format, in the manual and automated process case management system and prepare reports to management as required.
• Conduct quality reviews through our Investigative Excellence program to ensure the casework of L1 investigators meets our internal quality assurance requirements and regulatory expectations
• Regularly exercise good judgement in making decisions or recommendations in relation to case investigations and employee escalations from within your team.
• Work closely with senior leaders and PayPal’s People Team to utilize proper corrective action procedures as required.
• Work closely with senior leaders on projects and tasks as the business requires
• Maintain and grow subject matter expertise in PayPal’s investigations and processes
• Schedule, prepare, and lead 1:1 coaching, scheduled team learning sessions and leverage other best practices to ensure that you are driving interactive, engaging, and analyst-driven discussions based upon developmental needs of the team.
• Assessing team performance and providing feedback, development opportunities and oversight of action plans aimed at improving performance as needed

Expected Qualifications:

• 5 years of relevant work experience

Our Benefits:

Any general requests for consideration of your skills, please

Essential Responsibilities:

• Develop staffing models, create schedules, and monitor performance metrics.
• Identify trends, issues, and opportunities through key metrics analysis and develop improvement recommendations.
• Ensure high-quality baseline demand forecasts are developed and maintained for Operations.
• Serve as a subject-matter expert on workforce optimization issues and tools.
• Collaborate closely with leaders and other support functions to provide strategic insights to maximize utilization of staff.
• Make judgment calls based on data and sometimes incomplete data, displaying a heightened level of accountability, demonstrating a sense of responsibility, confidentiality and professionalism.

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 the development and optimization of advanced machine learning models.
• Oversee the preprocessing and analysis of large datasets.
• Deploy and maintain ML solutions in production environments.
• Collaborate with cross-functional teams to integrate ML models into products and services.
• Monitor and evaluate the performance of deployed models, making necessary adjustments.

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.

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

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