Develop and track metrics to measure and monitor the performance of our risk products and the effectiveness of risk management strategies.
Conduct in-depth analyses to uncover valuable insights contributing to fraud reduction and higher approval rates for our clients.
Serve as a client-facing partner by translating complex data insights into clear, actionable recommendations
Build and experiment with ML models to identify fraudulent patterns and enhance fraud detection capabilities.
Work with engineers on data instrumentation.
Create and automate self-serve dashboards leveraging BI tools.
Collaborate with cross-functional teams (Business, Product, and Engineering) to understand and translate business requirements into actionable data-driven solutions.
Collaborate on implementing risk mitigation solutions, ensuring alignment with business goals.

Strong technical background with 7+ years of experience demonstrating high impact in a data-focused role such as product analytics, business analytics, or data science
Prior experience in the Fraud/Risk domain
Hands-on experience in SQL and Python
Expertise in BI tools such as Tableau/Sigma/Metabase
Exposure to building ML models to address business challenges
Ability to structure and analyze data, leveraging techniques like EDA and cohort analysis, transform them into understandable and actionable recommendations, and then communicate them effectively across the organization and clients.
Proficiency in defining, utilizing, and communicating performance metrics
Creative problem-solving, strong critical thinking, and a getting-things-done approach

Data Scientist – Post Sales

Key skills