Staff Data Scientist – Trust and Safety

The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.

Company Overview

A leading global technology company is building one of the world’s most secure and advanced platforms for data and artificial intelligence. The organization develops innovative solutions in security, compliance, governance, and machine learning, enabling businesses worldwide to securely manage, analyze, and protect their data at scale. Its engineering teams leverage cutting-edge AI technologies while maintaining enterprise-grade security, reliability, and compliance across global cloud environments.

The organization is seeking a Staff Data Scientist – Trust and Safety to join its Trust and Safety Data Science team. This role focuses on developing advanced data science and machine learning solutions that strengthen platform security, detect fraud and abuse, improve compliance, and protect customer data. The successful candidate will collaborate closely with engineering, security, and product teams to deliver scalable, data-driven solutions that support millions of workloads across global cloud infrastructure.

The ideal candidate is an experienced data science leader with strong expertise in machine learning, statistical modeling, software engineering, and large-scale analytics. This position offers the opportunity to influence strategic security initiatives, mentor junior data scientists, and contribute to building one of the world’s most trusted AI and data platforms.

Key Responsibilities

• Develop and deploy machine learning models to detect anomalous and suspicious activity across platform products.
• Analyze the performance and pricing of security-related features and identify opportunities for optimization.
• Collaborate with security engineers, trust and safety specialists, and machine learning engineers to build systems that protect customers and business operations from fraud and threats.
• Design scalable analytical frameworks and solutions that support regulatory and compliance requirements.
• Gather business requirements and define project objectives, milestones, and measurable outcomes.
• Communicate technical findings and project progress to both technical and non-technical stakeholders.
• Mentor junior data scientists and interns through project planning, technical guidance, code reviews, and documentation reviews.
• Advocate for data-driven decision-making across the organization.
• Represent the data science organization at industry conferences, technical events, and academic engagements.

Required Qualifications

• 7+ years of experience in data science, machine learning, and advanced analytics within high-growth technology environments.
• Strong understanding of software engineering best practices, including testing, code reviews, and production deployment.
• Experience collaborating effectively with cross-functional engineering, product, and business teams.
• Proven experience deploying machine learning and data science solutions into production environments.
• Strong programming skills in SQL and Python or another modern programming language.
• Experience working with distributed data processing technologies such as Apache Spark.
• Knowledge of software engineering principles for scalable data applications.
• Experience applying machine learning and analytics to detect SaaS product misuse and improve compliance is preferred.
• Master’s degree or higher in a quantitative discipline, or equivalent industry experience.

Disclaimer

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