Staff Data Scientist

As a Staff Data Scientist at ServiceNow, you’ll play a highly embedded and influential role within our Data Science organisation, partnering closely with Development and Product teams across multiple products within ITOM. Rather than simply responding to predefined requirements, you’ll bring your own creativity, domain expertise, and ideas to identify opportunities, challenge assumptions, and solve complex problems using real customer data.

What you get to do in this role:

• Lead the development and evolution of advanced data science and machine learning capabilities, including noise reduction, anomaly detection, root cause analysis, and new AI-powered product features.
• Own complex data science problems end-to-end, from problem definition and ideation through experimentation, model development, evaluation, productionization, and deployment.
• Develop advanced algorithms and models using techniques such as machine learning, deep learning, NLP, anomaly detection, and statistical modeling.
• Partner closely with Product, Engineering, Quality, and Architects to translate product requirements into scalable, reliable ML solutions.
• Drive technical direction and mentor other data scientists, contributing to best practices in modeling, experimentation, evaluation, and ML engineering.
• Stay current with advances in AI/ML and identify opportunities to apply emerging technologies to ServiceNow products.

To be successful in this role you have:

• Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving.
• 6+ years of experience in data science, machine learning, algorithm development, or a related field.
• Advanced expertise in at least one area such as anomaly detection, machine learning, deep learning/neural networks, NLP, or statistical modeling.
• Proven experience leading complex data science or machine learning problems from ideation to production.
• Strong Python skills and hands-on experience with modern data science and ML frameworks.
• Experience working with large and complex datasets, developing evaluation methodologies, and defining metrics for ML models and data-driven products.
• Practical experience with modern AI/ML techniques, including LLMs and/or generative AI.
• Strong technical leadership, problem-solving, communication, and cross-functional collaboration skills.