Manager, Data Science, Fraud Incidents

PayPal•Austin, TX

12d

About The Position

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. Lead a team of Fraud Incident Responders responsible for complex data analysis in support of fraud incident management and FIRM's broader program, providing clear direction on priorities, methods, and quality standards. Act as a player-manager by personally owning the most complex or high-impact fraud incidents and regulatory reports, from scoping and data acquisition through analysis, insights, and communication of findings. Leverage data science and analytics to identify complex fraud patterns and their technical root causes through detailed data mining, enrichment, and correlation across large, multi‑source datasets. Provide rigorous quality assurance and technical leadership on BigQuery/SQL, Python, and other analytical tools and queries, uplifting code quality, performance, documentation, testing, and reproducibility across the team. Design and maintain reusable analytical assets (standard queries, parameterized notebooks, curated datasets, dashboards) and investigation templates that enable faster, more consistent, and higher‑quality fraud investigations. Drive programmatic initiatives that enhance FIRM's fraud analytics capabilities, including improving data models and taxonomies, creating and refining KPIs/KRIs, and automating manual, error‑prone workflows. Partner closely with Incident Managers to align analytical outputs with incident narratives, root-cause analysis, and remediation plans, ensuring a consistent and data-driven view of incidents across the program. Collaborate with Legal, Regulatory Relations, Compliance, Audit, and other stakeholders to translate regulatory obligations into clear data and reporting requirements, ensuring that datasets and reports are accurate, complete, and auditable. Use innovation and outside-the-box thinking to create new analytical capabilities, methods, and processes—particularly for unstructured or exploratory problem spaces and emerging fraud trends and typologies. Develop and maintain strong cross-organization relationships, collaborating and communicating effectively with business, risk, engineering, and technology stakeholders across multiple geographies. Coach, mentor, and develop analysts through structured feedback, code reviews, technical training, and career development planning, building deep expertise in financially motivated cybercrime, incident analytics, and regulatory reporting. Prioritize and balance team capacity between urgent incident investigations and longer‑term program development initiatives, ensuring sustainable workload management and consistent delivery of high‑quality analytical outputs. Champion a culture of curiosity, continuous improvement, and operational excellence, incorporating lessons learned from incidents into playbooks, tooling, documentation, and training for the broader FIRM organization.

Requirements

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

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.
Lead a team of Fraud Incident Responders responsible for complex data analysis in support of fraud incident management and FIRM's broader program, providing clear direction on priorities, methods, and quality standards.
Act as a player-manager by personally owning the most complex or high-impact fraud incidents and regulatory reports, from scoping and data acquisition through analysis, insights, and communication of findings.
Leverage data science and analytics to identify complex fraud patterns and their technical root causes through detailed data mining, enrichment, and correlation across large, multi‑source datasets.
Provide rigorous quality assurance and technical leadership on BigQuery/SQL, Python, and other analytical tools and queries, uplifting code quality, performance, documentation, testing, and reproducibility across the team.
Design and maintain reusable analytical assets (standard queries, parameterized notebooks, curated datasets, dashboards) and investigation templates that enable faster, more consistent, and higher‑quality fraud investigations.
Drive programmatic initiatives that enhance FIRM's fraud analytics capabilities, including improving data models and taxonomies, creating and refining KPIs/KRIs, and automating manual, error‑prone workflows.
Partner closely with Incident Managers to align analytical outputs with incident narratives, root-cause analysis, and remediation plans, ensuring a consistent and data-driven view of incidents across the program.
Collaborate with Legal, Regulatory Relations, Compliance, Audit, and other stakeholders to translate regulatory obligations into clear data and reporting requirements, ensuring that datasets and reports are accurate, complete, and auditable.
Use innovation and outside-the-box thinking to create new analytical capabilities, methods, and processes—particularly for unstructured or exploratory problem spaces and emerging fraud trends and typologies.
Develop and maintain strong cross-organization relationships, collaborating and communicating effectively with business, risk, engineering, and technology stakeholders across multiple geographies.
Coach, mentor, and develop analysts through structured feedback, code reviews, technical training, and career development planning, building deep expertise in financially motivated cybercrime, incident analytics, and regulatory reporting.
Prioritize and balance team capacity between urgent incident investigations and longer‑term program development initiatives, ensuring sustainable workload management and consistent delivery of high‑quality analytical outputs.
Champion a culture of curiosity, continuous improvement, and operational excellence, incorporating lessons learned from incidents into playbooks, tooling, documentation, and training for the broader FIRM organization.