Data Scientist

What You’ll Do

• Analyze and interpret complex data sets to derive actionable insights and inform decision-making.
• Perform statistical analysis on feature transformation and business impact analytics.
• Standardize rules and decision processes while enabling dynamic rule updates and analytics within the fraud detection platform.
• Collaborate across multidisciplinary teams in engineering, product development, and data science to scale solutions globally.

Story Behind the Need – Team & Key Projects

• Team: Work closely with Core Automation team’s tech leads/managers.
• Partner with engineering teams to rebuild the next-generation risk platform (NGRP).
• Be part of the pioneer team launching NGRP.

Reason for Posting:
Building a next-generation risk platform to support enterprise business functions under tight timelines for decision engine adoption.

**Typical Day in the Role

Daily Responsibilities:**

• Test and evaluation; processing and governance; monitoring.
• Data analysis and decision engine serving 80+ checkpoints—ensure all rules perform with high quality; troubleshoot and automate when issues arise.
• Tasks distributed via Jira board (sprint planning/grooming cycle).
• Regular standups (at least twice a week; daily if needed).
• Onboarding requires more interaction with Engg/Product/US Risk core teams; later, ~50/50 split.
• Work primarily within Jira for task assignments and tracking.
• Code maintained in centralized GitHub repo.
• Documentation in wiki pages or SharePoint/shared drives.

Compelling Story & Candidate Value Proposition

• Why this role is interesting: Design and implement scalable solutions to optimize fraud detection systems, spanning model development, feature engineering, and rule-based systems.
• Collaborate closely with cross-functional teams to set a new global standard for efficacy and innovation.
• Address critical business challenges, develop advanced automation frameworks, and integrate cutting-edge machine learning techniques to enhance decision-making capabilities.

Candidate Requirements

• Top 3 Must-Have Skills (stack-ranked):

1. BigQuery, Python
2. Understanding of production systems architecture and offline data overview
3. Machine Learning experience

• Nice to Have: Risk and fraud experience or business acumen; experience working directly with engineers.
• Years of Experience: 6+
• Degrees/Certifications: Master’s preferred; solid BS acceptable (STEM only).

Compensation: $50-$55/hour