Data Scientist
Credit Key- Full Time
- Junior (1 to 2 years)
Candidates should possess a Bachelor's or Master's degree in Data Science, Statistics, Mathematics, or a related quantitative field, along with at least one year of hands-on experience in data science, risk analytics, fraud detection, or a similar field. Proficiency in SQL and data wrangling for large and complex datasets is required, as well as experience with Python or R and relevant libraries such as pandas, scikit-learn, tidyverse, ggplot2, XGBoost, and statsmodels. A solid understanding of supervised and unsupervised learning techniques, including anomaly detection, classification, and clustering is also necessary.
The Data Scientist will design and develop risk models and anomaly detection algorithms to monitor merchant behavior and flag high-risk activity, applying machine learning, statistical modeling, and time series analysis to detect patterns and trends in large datasets. They will translate business problems into data science solutions through collaboration with risk, engineering, and product teams, continuously evaluate and improve model performance, and develop dashboards, visualizations, and reports to communicate insights to non-technical stakeholders.
High-performance payments platform for enterprises
Checkout.com provides a payments platform that helps businesses process payments, send payouts, and manage card programs. The platform is designed for large enterprises and growing businesses, allowing them to handle high volumes of transactions quickly and reliably. It integrates with clients' existing systems and offers a range of payment services, generating revenue through transaction fees and subscriptions. Unlike many competitors, Checkout.com focuses on providing a comprehensive, cloud-based solution that supports the financial operations of its clients across the globe. The goal of Checkout.com is to streamline payment processes and enhance the payment experience for both businesses and their customers.