- Company Name
- PayPal
- Job Title
- Sr Data Scientist
- Job Description
-
**Job Title:** Sr Data Scientist
**Role Summary:**
Lead the design, implementation, and continuous improvement of advanced predictive models and analytics strategies that protect PayPal Credit products from fraud. Own end‑to‑end fraud prevention initiatives, leveraging large, complex datasets to balance user experience, operational cost, and loss exposure while driving business profitability.
**Expectations:**
- Manage the full lifecycle of fraud‑risk analytics projects, from hypothesis to production deployment.
- Collaborate cross‑functionally with risk, product, operations, legal, and compliance teams to define requirements and align strategy.
- Maintain rigorous data quality standards and ensure integrity across all data pipelines.
- Mentor and coach junior data scientists, fostering a culture of best practices and continuous learning.
- Stay current with emerging techniques and industry trends in data science and fraud detection.
**Key Responsibilities:**
- Conceive, build, and iterate machine‑learning and statistical models for fraud detection and loss mitigation.
- Design risk‑management frameworks that identify and close gaps in existing fraud controls.
- Monitor model performance, conduct root‑cause analysis, and implement optimizations to meet defined SLAs.
- Translate complex analytical findings into clear, actionable recommendations for technical and non‑technical stakeholders.
- Communicate results and strategic insights to leadership, partners, and cross‑functional teams.
**Required Skills:**
- 5+ years of proven experience in credit or fraud‑risk analytics.
- Expertise in statistical modeling, machine‑learning algorithms, and feature engineering (e.g., tree‑based models, gradient boosting, deep learning).
- Proficiency in Python, R, SQL, and big‑data tools (Spark, Hive, etc.).
- Strong analytical and problem‑solving abilities with meticulous attention to detail.
- Excellent written and oral communication; ability to present complex concepts to diverse audiences.
- Business acumen and strategic thinking to balance user experience, cost, and risk.
**Required Education & Certifications:**
- Bachelor’s degree or higher in Mathematics, Statistics, Operations Research, Finance, Economics, or a related quantitative discipline.
- Any relevant certifications in data science, statistics, or fraud‑risk domains are a plus.