Data Science Leader

2 weeks ago

Dublin, Dublin City, Ireland beBeeRiskManagement Full time
Job Title:
Data Science Manager

This role is responsible for leading the development and improvement of risk strategies using both proprietary tools and custom AI/ML models. As a Data Science Manager, you will partner closely with business units to align on strategic priorities, educate partners about core risk-management principles, and collaboratively optimize risk treatments and experiences across products.

The ideal candidate will have 8+ years of experience working with large-scale datasets, including at least 3 years managing a team of 3-6 data scientists in a fraud-risk or financial services environment. They will be proficient in SQL and Python (or R) for data wrangling, EDA, and model development, and have hands-on experience applying supervised and unsupervised learning techniques.

They will also have a deep understanding of fraud-risk principles, including AML/KYC, regulatory compliance, and performance metrics. The candidate should be able to distill complex findings into clear narratives for both technical and non-technical audiences.

Responsibilities:

  • Portfolio Ownership: Lead a group of data scientists to manage fraud and loss metrics for assigned product lines or markets.
  • Strategy Development: Collaborate cross-functionally to develop and iterate on fraud-prevention frameworks that optimize transaction declines and minimize customer friction.
  • Model Lifecycle Management: Guide the team in data preparation, feature engineering, model training, and validation—leveraging Python/R and cloud-native platforms.
  • Stakeholder Alignment: Host regular syncs with business units, risk operations, and compliance to ensure models and business rules remain aligned with evolving policy and regulatory requirements.
  • Performance Monitoring: Track model health (drift, false-positive/false-negative rates) and lead root-cause analyses for any anomalies or spikes in loss.

Requirements:

  • Advanced proficiency in SQL and Python (or R) for data wrangling, EDA, and model development.
  • Hands-on experience applying supervised and unsupervised learning techniques (regression, classification, clustering, decision trees, anomaly detection).
  • Familiarity with production ML frameworks (scikit-learn, TensorFlow, PyTorch) and cloud data platforms (BigQuery, Snowflake).
  • Deep understanding of fraud-risk principles, including AML/KYC, regulatory compliance, and performance metrics.
  • Strong track record of partnering with engineers, product managers, and business leaders.

Benefits:

  • A flexible work environment, employee stock options, health and life insurance, and more.
  • Our balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace.

Commitment to Diversity and Inclusion:

PayPal provides equal employment opportunity to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law.

Belonging at PayPal:

Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging.

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