• If you have a foundation in online platform trust and safety issues, skills in data science and machine learning and an empathetic approach to mentoring and collaborating with a diverse team from entry-level associates to seasoned senior contributors then this might be the gig for you
• 2+ years of experience operationalizing machine learning and data science
• 1+ year experience in any of these technologies: GraphQL, Flink, Python, SQL, Azure Machine Learning, Kusto
• 1+ year experience in Data Visualization, Data Storytelling or other strong written and verbal communication skills

Desirable

• We're looking for an experienced machine learning expert to help train, test and deploy models as well as conduct ad-hoc analysis as they protect the home of all developers
• You will be responsible for identifying new trends relating to safety, fraud and abuse on GitHub, building models to detect this abuse at scale, identifying vulnerabilities in GitHub that lead to abuse and helping to measure the impact of our work to safeguard the platform
• At GitHub, Platform Health’s mission is to ensure GitHub’s platform safety through fighting malware, spam and fraud, monitoring for fake accounts, countering inauthentic content, battling crypto mining, and other core areas
• You will be involved in collaborations across teams within GitHub including with CoPilot and setting the standard for effective and responsible use of AI for moderation and trust and safety purposes ensuring fraud is countered, content is moderated, users are kept safe and the open-source community can flourish
• Conduct thorough analysis of data to identify patterns, trends, and anomalies that indicate potential risks or fraudulent behavior
• Develop and implement machine learning models and algorithms to detect and prevent fraudulent activities, abuse, and security threats
• Utilize Azure Machine Learning services and other relevant technologies to build scalable and reliable machine learning workflows
• Documenting the systems you help build
• Encouraging the technical growth of your peers
• Collaborate closely with cross-functional teams including data scientists, software engineers, product managers and content moderators to integrate machine learning solutions into production systems
• Evaluate and improve existing machine learning models and algorithms based on performance metrics and feedback from operational deployments
• Identifying the vulnerabilities in products that lead to abuse
• Reviewing new products and providing consultation to product teams
• Stay updated with the latest advancements in machine learning, fraud detection techniques, and security protocols to continuously enhance our capabilities
• Job level: Individual Contributor