Description

Key Skills: Deep Learning, Machine Learning, Python, Data Analysis, Fraud Detection, Self-Supervised Learning, Representation Learning, Clustering, Time Series Analysis, Anomaly Detection

Good to Have Skills: Experience with Amazon cloud services including EC2, S3, EMR, Sagemaker, and RedShift. Knowledge of generative modeling, multi-modal representation learning, sparse labeling methods, and advanced clustering techniques. Experience with processing petabyte-scale data and working with unstructured datasets. Background in advertising fraud detection and invalid traffic detection systems.

Roles & Responsibilities:

• Deliver on new research problems in fraud detection where neither problem nor solution is well-defined.
• Invent and adapt new machine learning approaches, models, and algorithms to detect sophisticated invalid traffic.
• Design and deploy production-quality ML components that directly impact advertiser trust and the business top-line.
• Apply domain knowledge to perform broad data analysis as a precursor to modeling and build business insights.
• Work with unstructured and massive datasets to deliver results at petabyte scale processing billions of events daily.
• Produce research reports meeting top-tier external publication standards for the scientific community.
• Contribute to the scientific community through publications at peer-reviewed venues and reviewing research submissions

Key Skills

Education

Any Graduate