Vana
51 - 200 employees
Founded 2018
💳 Fintech
🛍️ eCommerce
👥 B2C
💰 Seed Round on 2020-07
Fintech • eCommerce • B2C
Vana is a digital lending platform that allows users to easily apply for and receive personal loans directly from their mobile devices. The application offers fast approval times and deposits funds into users' bank accounts, ensuring a seamless experience for borrowing up to Q2,500. Vana prioritizes user security by adhering to industry standards for data protection, and it promotes financial growth by enabling users to increase their credit limits with timely repayments. Vana is a member of the Fintech Association of Guatemala, reflecting its commitment to providing reliable and efficient financial services.
Fraud Data Scientist
Job not on LinkedIn
🕒 March 19
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Vana
51 - 200 employees
Founded 2018
💳 Fintech
🛍️ eCommerce
👥 B2C
💰 Seed Round on 2020-07
Fintech • eCommerce • B2C
Vana is a digital lending platform that allows users to easily apply for and receive personal loans directly from their mobile devices. The application offers fast approval times and deposits funds into users' bank accounts, ensuring a seamless experience for borrowing up to Q2,500. Vana prioritizes user security by adhering to industry standards for data protection, and it promotes financial growth by enabling users to increase their credit limits with timely repayments. Vana is a member of the Fintech Association of Guatemala, reflecting its commitment to providing reliable and efficient financial services.
📋 Description
• Data analysis and modeling: Explore large-scale transactional and behavioral datasets to uncover patterns associated with fraud. • Model development and validation: Build and validate classification models using ML techniques tailored to imbalanced problems (fraud vs. non-fraud). • Feature engineering: Create derived variables that enhance model performance and generalization while avoiding overfitting. • Cross-functional collaboration: Work with engineering, product, and operations teams to ensure seamless integration of models into decision flows. • Monitoring and iteration: Track model performance in production and iterate based on behavioral changes, fraud trends, or strategy shifts. • Research and innovation: Stay up to date on cutting-edge ML techniques for fraud detection in digital transactional environments.
🎯 Requirements
• Degree in Data Science, Statistics, Mathematics, Computer Science or a related field with strong programming skills [MUST] • 1-2 years of experience in Data Science, Data/Business Analytics (with ML knowledge) [MUST] • 2+ years of Python and SQL experience [MUST] • Knowledge of fraud detection, anomaly detection, or modeling with imbalanced datasets [MUST] • Industry background in fintech, insurance, or banking is valued but not required [DESIRABLE] • AWS Services knowledge is a Plus [DESIRABLE] • Strong analytical skills and a problem-solving mindset, with the ability to extract actionable insights from data [MUST] • Understanding of consumer behavior, alternative data sources, and digital lending platforms [DESIRABLE]
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