Senior Data Scientist

ServiceNow · San Francisco

Data & AIFull-timeposted 6w ago

Company Description

It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started.

Join us to put AI to work for people.

Job Description

What you get to do in this role:

Partner with executive, product and engineering teams to define and govern Moveworks’ critical product metrics, ensuring consistency, accuracy, and alignment across the company.
Apply rigorous statistical and machine learning techniques to unearth the critical levers that drive our core metrics. Your insights will be the bedrock of our product initiatives, and you will be accountable for forecasting and measuring the impact of these initiatives on business outcomes.
Analyze and measure core engineering system performance, isolating signal from noise by controlling for confounding variables (e.g., usage patterns, resource supply, and skill activation).
Lead the design, development, and ownership of best practices, tools, and processes for building scalable and robust analytical systems. These systems will automate established analyses and empower cross-functional partners with self-serve insights.
Drive the development of DS workflow and AI-native integrations (e.g., Superset MCP, Claude integrations) that extend self-serve data access and reduce time-to-insight for stakeholders.
Provide technical mentorship to junior data scientists and contribute to hiring and team-building, establishing best practices for data modeling, pipeline design, and evaluation methodology.

Qualifications

To be successful in this role you have:

M.S. or Ph.D. in Data Science, Computer Science, Statistics, or a related quantitative field, plus 5+ years of progressive experience building and deploying production analytics or ML solutions for enterprise software products.
Demonstrated expertise in LLM evaluation methodology, including dataset curation, benchmarking, and regression detection for AI/LLM systems.
Proven experience architecting scalable data pipelines using distributed systems (e.g., PySpark/Spark SQL), orchestration frameworks (e.g., Airflow), and cloud platforms (e.g., AWS EMR, S3, Snowflake or equivalent).
Proficiency in Python and SQL; track record of translating complex analytical work into measurable business outcomes and operational KPIs.
Demonstrated ability to lead technical workstreams and drive cross-functional alignment.
Experience providing technical leadership and mentoring to data scientists or engineers.
Experience building evaluation pipelines or harnesses for agentic or LLM-powered systems.
Experience with conversational analytics, NLP, or AI-assisted data exploration tooling.
Prior work on self-serve analytics platforms or customer-facing data products at enterprise scale.
Experience using modern AI productivity tooling (e.g., Claude, Cursor, Codex) within an enterprise SDLC.

For positions in this location, we offer a base pay of $161,300 - $274,200, 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 based on work location.

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 globaltalentss@servicenow.com 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.