Experian's product aims to prevent the creation of fraudulent accounts for online banks, lenders, and other financial services providers by tracking user interactions on their devices. The Customer Analytics Data Scientist will analyze data and present results to clients to optimize performance and support expansion opportunities, bridging the gap between revenue and technical departments to promote revenue generation and retention.
Requirements
- Proficiency in handling large datasets using SQL and Python.
- Experience with data analytics software and tools, including Snowflake, Looker, and GitHub.
- Experience fraud detection, data analysis, or a related field.
Responsibilities
- Conduct prospect-facing technical analysis to compute and present Return on investment for all sales engagements.
- Perform technical analysis for existing clients and present results to optimize performance and support expansion opportunities.
- Bridge the gap between revenue and technical departments to promote revenue generation and retention.
- Collaborate with Sales, Client Success, Product, and Implementation Engineering teams to understand customer use cases and application flows
- Distill customer needs and revenue opportunities into achievable technical milestones, guiding Data Science and Engineering development efforts.
- Support the Sales Engineering team in guiding customer analyses to win proof of value trials, convert prospects to clients, and expand customer usage.
- Create enablement materials, including best practices, reference guides, FAQs, video content, and analysis walk-throughs, to coach customers and partners on realizing and quantifying value.
Other
- Comfortable presenting results internally and externally.
- Bachelor's degree in a quantitative field such as Finance, Statistics, Mathematics, Operations Research, Engineering, Computer Science.
- 3+ years of experience in fraud management, fraud strategy, or fraud operations, developing fraud prevention strategies and procedures.
- Flexible work environment, ability to work remote, hybrid or in-office
