Data Scientist
Sardine- Full Time
- Senior (5 to 8 years)
Candidates should possess a degree in Statistics, Machine Learning, Computer Science, Applied Mathematics, Operations Research, or a related field, with at least six years of experience working with large datasets using tools such as Jupyter, Pandas, PySpark, PyTorch, or TensorFlow, and at least four years of experience applying AI/ML methodologies in a production environment. Strong proficiency in Python and experience building analytical tools are also required.
The Senior Data Scientist will research and analyze gaps in machine learning models, summarize emerging fraudulent behavior patterns, define success metrics, propose targeted improvements to enhance model performance, collaborate with engineers to build scalable ML models, develop systems that explain model predictions, communicate effectively to influence stakeholders, leverage anomaly detection algorithms, and ultimately enable low-latency, large-scale fraud prevention for customers.
Real-time fraud detection and prevention platform
Sift provides a platform focused on detecting and preventing online fraud in real-time, catering to clients in e-commerce, fintech, and digital marketplaces. The platform uses machine learning and artificial intelligence to analyze large datasets, allowing it to identify fraudulent activities effectively. One of its standout features is dynamic friction, which ensures that genuine users have a smooth experience while preventing fraudsters from accessing services. Sift's business model is subscription-based, with fees that depend on transaction volume and service level. Additionally, Sift offers services like chargeback management and dispute resolution, which add further value to its offerings. The company's goal is to enhance digital trust and safety for businesses by providing tools that help them make informed decisions and protect against fraud.