Data Scientist

About Tapper

Tapper prevents ad fraud by detecting and blocking invalid traffic in real time. Using machine learning and behavioral analysis, we identify bots, competitors, and fraudulent clicks to optimize ad spend. Our system integrates directly with ad platforms, ensuring marketing budgets drive real engagement, not waste.

Key Responsibilities

• Develop and optimize ML and deep learning models for fraud detection in digital advertising.
• Analyze user behavior patterns to identify anomalies and fraudulent activity.
• Work with large-scale tabular data, applying unsupervised learning techniques.
• Build and maintain scalable data pipelines using SQL and NoSQL databases.
• Deploy, monitor, and optimize ML models on AWS cloud services.
• Stay ahead of evolving fraud tactics and continuously refine detection strategies.

Must-Have Skills

• 3+ years of experience in data science, machine learning, or a related field.
• Strong foundation in ML, deep learning, and statistical analysis.
• Proficient in Python, writing efficient, scalable, and structured code.
• Experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Hands-on expertise in fraud detection using tabular data and anomaly detection techniques.
• Experience with SQL and NoSQL databases for large-scale data processing.
• Proven experience deploying ML models in AWS environments.

Nice-to-Have Skills

• Experience with AWS SageMaker for training and deployment.
• Strong code optimization skills for performance and scalability.
• Domain knowledge in digital advertising fraud detection.

Interested? Email us at join@tapper.ai