
Staff Data Scientist
- San Jose, CA
- Permanent
- Full-time
Adobe offers an outstanding opportunity to join Adobe's Risk Platform team as a Staff Data Scientist!
In this role, you will infuse data and insights into every product development phase to detect fraud trends, automate processes, and provide data driven insights to protect Adobe’s revenue and maintain customer trust. As a technical leader, you'll drive discussions at the intersection of data science and product management, working with different partners across Adobe to build best in class fraud detection capabilities.What you'll Do
- Detect emerging fraud and abuse across various platforms and products.
- Automate manual workflows to build efficiencies and scale up fraud prevention, investigations and operational workflows.
- Expert in data analyses and improve tools and processes through technical expertise.
- Sound data visualization skills with ability to tell the story to key partners.
- Translate investigations and intel into root cause analysis to find opportunities for scale.
- Advanced degree (Masters or Ph.D.) in Computer Science, Statistics, Mathematics, or related quantitative field, or equivalent work experience with a Bachelor's degree.
- 8+ years of proven experience in data science, machine learning, with a focus on fraud detection or risk management in subscription-based businesses or financial services.
- Expertise in machine learning techniques, including supervised and unsupervised learning, anomaly detection, and ensemble methods.
- Proficiency in programming languages such as SQL, Python or R.
- Proficiency in technologies related to large-scale datasets and distributed computing frameworks (e.g., Hadoop, Spark).
- Exposure to using Ai agents and LLM (Large Language Model) for any of the projects.
- Excellent communication and leadership skills, with the ability to collaborate effectively with cross-functional teams and drive alignment on fraud detection strategies.
- Proven track record of leading complex data science projects from conception to production deployment, delivering tangible business value.
- Experience with fraud detection tools and platforms (e.g., fraud detection APIs, fraud management systems) is highly recommended.