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ServiceNow is seeking a Staff Data Scientist to join its Data Science organization, working within the ITOM (IT Operations Management) product suite. This is a highly embedded, influential role where you'll partner closely with Development and Product teams to identify opportunities, challenge assumptions, and solve complex problems using real customer data.
In this role, you will:
- Lead the development and evolution of advanced data science and machine learning capabilities, including noise reduction, anomaly detection, root cause analysis, and 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 machine learning, deep learning, NLP, anomaly detection, and statistical modeling techniques
- Partner with Product, Engineering, Quality, and Architects to translate requirements into scalable, reliable ML solutions
- Drive technical direction and mentor other data scientists, establishing best practices in modeling, experimentation, evaluation, and ML engineering
- Stay current with AI/ML advances and identify opportunities to apply emerging technologies to ServiceNow products
ServiceNow is the AI control tower for business reinvention, serving 85% of the Fortune 500. The company is building an AI-native culture where technology and talent work together to automate busywork and enable meaningful work.
REQUIREMENTS:
- 6+ years of experience in data science, machine learning, algorithm development, or related field
- Advanced expertise in at least one area: 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
- Experience leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving
- Strong technical leadership, problem-solving, communication, and cross-functional collaboration skills
