Senior Data Scientist

ServiceNow•Mountain View, CA

19d•Remote

About The Position

This role involves partnering with executive, product, and engineering teams to define and govern critical product metrics, ensuring consistency, accuracy, and alignment across the company. The Senior Data Scientist will apply rigorous statistical and machine learning techniques to identify key drivers of core metrics. Insights generated will form the basis of product initiatives, with accountability for forecasting and measuring their impact on business outcomes. The role also includes analyzing and measuring core engineering system performance, isolating signal from noise by controlling for confounding variables. A key responsibility is leading the design, development, and ownership of best practices, tools, and processes for building scalable and robust analytical systems to automate analyses and empower cross-functional partners with self-serve insights. Additionally, the role will drive the development of DS workflow and AI-native integrations to extend self-serve data access and reduce time-to-insight. The Senior Data Scientist will 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.

Requirements

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.

Nice To Haves

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.

Responsibilities

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.
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.
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.