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HUMAN's Sightline Enterprise Research and Detection team is seeking a Data Scientist to join their fraud and bot detection efforts. The team processes trillions of events per day and uses statistical and machine learning techniques to develop detection algorithms that protect enterprises from sophisticated bots, fraud, and account abuse.
In this role, you will support the full cycle of fraud fighting—from gathering business requirements and exploratory research through development and production deployment of statistical detection techniques. You'll work at the intersection of data, technology, and business, partnering with Product, Engineering, and Analysts to improve bot detection capabilities, build competitive product features, and optimize data and ML infrastructure.
Key responsibilities include:
- Researching and experimenting with the latest detection frameworks in cybersecurity and fraud, statistical techniques, and ML tooling
- Developing and deploying statistical detection techniques in production systems
- Supporting the growth of best practices and Data Science standards in detection and modeling
- Participating in code reviews (the 'sheriffing' process) to monitor anomalies in systems
- Contributing to software tooling and automation that creates leverage for the team
- Collaborating across cross-functional teams with both technical and non-technical stakeholders
HUMAN was founded with a mission to make the internet safer by putting humans first. The company's Human Defense Platform safeguards enterprises by verifying the humanity of more than 20 trillion interactions per week. The company is headquartered in NYC with teams worldwide and offers flexible work options.
Requirements:
- Experience solving large-scale, data-intensive problems in production systems; literacy with large datasets is essential
- Strong understanding of statistical modeling approaches and ability to make informed decisions on which techniques to use
- Engineering awareness of the realities of shipping working code to customers
- Proficiency with Python and SQL; familiarity with related tools, libraries, and platforms
- Fluency in Object-Oriented development and strong debugging skills
- Experience working on cross-functional projects with multiple stakeholders
- Familiarity with SDLC best practices: project management, version control, unit testing, and CI/CD
- Strong sense of ownership and accountability for work quality and accuracy
