Senior Staff Demand Planning at ServiceNow

New York, New York, United States -

Full Time

Start Date

Immediate

Expiry Date

11 Feb, 26

Salary

346200.0

Posted On

13 Nov, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Java, AI, ML, Time Series Modeling, Regression, Bayesian Forecasting, Econometrics, TensorFlow, PyTorch, Spark, Hive-Hadoop, Data Visualization, Tableau, Excel, BI Tools

Industry

Software Development

Description

Company Description It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today — ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone. Job Description NOTE: This position requires passing a ServiceNow background screening, USFedPASS (US Federal Personnel Authorization Screening Standards). This includes a credit check, criminal/misdemeanor check and taking a drug test. Any employment is contingent upon passing the screening. Due to Federal requirements, only US citizens, US naturalized citizens or US Permanent Residents, holding a green card, will be considered. This role will require at min 2 days a week in the office. The Demand Planning team within ServiceNow’s FinOps organization is an innovative, customer-focused group responsible for capacity demand planning, forecasting, cost measurement, reporting, and analysis for ServiceNow's top-tier infrastructure. We aim to provide industry-leading work experiences for our customers. As an ML/AI engineer on the capacity planning team, you will collaborate with a data-centric group of data scientists, engineers, and capacity planners. Our mission is to scale ServiceNow's global rack, server, and data center capacity as and when required. The team plays a critical role in managing and forecasting customer demand while overseeing capacity planning and analytics for ServiceNow’s global infrastructure. This includes adjusting forecasting models to incorporate hybrid cloud strategies and fine-tuning them to adapt to new, multi-dimensional metrics—ensuring that ServiceNow’s global rack, server, and data center capacity is efficiently scaled as business needs evolve. Additionally, you will be instrumental in building and refining capacity forecasting models that utilize AI and Machine Learning (ML) techniques, as well as designing analytics tools to predict resource demand across diverse infrastructure environments. This includes proactively identifying capacity-related issues, leading experiments to determine scaling and utilization parameters for different service tiers, and incorporating multi-dimensional metrics into the models. The role requires close collaboration with hardware, capacity, infrastructure, platform engineering, and cloud analytics teams to develop comprehensive capacity roadmaps and deliver actionable insights for a variety of cloud capacity engineering initiatives, with a strong emphasis on supporting both traditional and hybrid cloud strategies. What you get to do in this role: Design, implement, and deploy AI/ML-driven capacity forecasting models for long-range demand and supply planning. Convert demand forecasts into actionable server and rack requirements. Enhance forecasting accuracy by incorporating multi-dimensional metrics and hybrid cloud strategies. Run forecast scenarios to optimize scaling and utilization across service tiers. Collaborate with hardware, infrastructure, and cloud analytics teams to develop capacity roadmaps. Track and report forecast variability, presenting insights to leadership. Apply advanced techniques (ARIMA, RNN, LSTM, NOW AI) to improve predictive models. Build analytics tools to identify bottlenecks and proactively address capacity issues. Qualifications 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. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry. 12 years of related experience with a Bachelor's degree; or 8 years and a Master's degree; or a PhD with 5 years experience in Computer Science, Data Analytics or related field; or equivalent experience. Technical Expertise: Programming: Python, Java; strong OOP and algorithmic skills. AI/ML: Time series modeling, regression, Bayesian forecasting, econometrics. Tools: TensorFlow, PyTorch, Spark, Hive-Hadoop, Big Data frameworks. Data Visualization: Python, Tableau, Excel, Lightdash, BI tools Experience in developing new products that utilize challenging high-performance algorithms. Expertise in coding efficient, object-oriented, modularized, and high-quality software. Expertise in core AI/ML techniques and algorithms. Understanding of unit testing, profiling, and code tuning. Additional Skills: ServiceNow platform architecture (CMDB, instance topology), unit testing, profiling, and code optimization. Strong communication and cross-functional collaboration skills. GCS-23 For positions in this location, we offer a base pay of $197,800 - $346,200, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change Additional Information Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact [email protected] for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2025 Fortune Media IP Limited. All rights reserved. Used under license.

Responsibilities

Design and implement AI/ML-driven capacity forecasting models for demand and supply planning. Collaborate with various teams to develop capacity roadmaps and enhance forecasting accuracy.