Key Responsibilities
Business Problem Discovery
- Partner with clients to understand business logic, decision flows, pain points, fraud patterns, data availability, data quality, and desired business outcomes
- Translate business challenges into actionable risk and solution requirements
Data Gathering and Integration
- Lead technical discussions with clients’ risk, fraud, AML, and data teams to ensure complete and high-quality data collection
- Own data transfer coordination and data quality validation
Data Analysis and Risk Strategy Development
- Conduct data analysis and fraud pattern analysis using strong domain expertise and business judgment
- Design, recommend, test, and iterate on detection strategies to improve risk outcomes
Solution Configuration
- Configure DataVisor platform components such as Rules Engine, Decision Flows, Case Management, Knowledge Graph, and BI Dashboards
- Deliver tailored solutions that generate strong business value for clients
ML Model Performance Analysis
- Partner with the ML Modeling team to develop, tune, and evaluate supervised and unsupervised fraud detection models
- Analyze model performance metrics and provide guidance on threshold setting and decisioning strategies
Project Management and Documentation
- Manage solution delivery projects using project management tools such as Monday.com
- Own the creation, maintenance, and reporting of key internal and customer-facing project deliverables
Presentation and Demonstration
- Present project findings, recommendations, and solution outcomes to business and technical stakeholders
- Demonstrate configured solutions and articulate business impact clearly and effectively
Requirements
Experience
- 4+ years of experience in fraud and/or AML strategy, analytics, or modeling
- 2+ years of experience leading client-facing data analytics or consulting projects
Technical Skills
- Strong domain knowledge of fraud and AML use cases within the financial services industry
- Advanced SQL skills, including complex joins and layered business logic
- Familiarity with Python, R, and Java is a plus
- Experience using LLM tools such as ChatGPT and Claude to accelerate research, problem-solving, and documentation
- Experience configuring technical products and debugging feature, rule, and result behavior
Soft Skills
- Excellent communication, presentation, and interpersonal skills
- Strong analytical, problem-solving, and results-oriented mindset
- Strong documentation discipline and interest in automation using AI tools and agents
- Ability to collaborate effectively in a fast-paced team environment and manage multiple projects simultaneously
Education
- Bachelor’s degree in a technical or analytical field such as Data Science, Statistics, Computer Science, or a related discipline
Benefits
- Stock options
- Medical insurance
- 401K
- PTO