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Senior Data Scientist - Moveworks

职能数据科学
级别资深
地点Mountain View
方式现场办公
类型全职
发布1周前
立即申请

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.

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., Py Spark/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.

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

Service Now 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), Service Now may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon Service Now 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.

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 — Service Now 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.

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关于ServiceNow

ServiceNow

ServiceNow, Inc. is an American software company that supplies a cloud computing platform for the creation and management of automated business workflows. The company was founded in Santa Clara, California, United States, in 2003 by Fred Luddy.

10,001+

员工数

Santa Clara

总部位置

$150B

企业估值

评价

10条评价

3.8

10条评价

工作生活平衡

2.8

薪酬

3.7

企业文化

4.1

职业发展

3.4

管理层

3.2

72%

推荐率

优点

Supportive and collaborative team environment

Good training and development opportunities

Flexible work arrangements

缺点

Work-life balance challenges and heavy workload

Fast-paced and stressful work environment

Management and communication issues

薪资范围

59个数据点

Junior/L3

Mid/L4

Senior/L5

Staff/L6

Junior/L3 · Data Informatics Analyst

1份报告

$87,176

年薪总额

基本工资

$67,059

股票

-

奖金

-

$87,176

$87,176

面试评价

6条评价

难度

3.0

/ 5

时长

14-28周

录用率

17%

面试流程

1

Application Review

2

Recruiter Screen

3

Behavioral Interview

4

Technical Interview

5

Final Round

6

Offer

常见问题

Coding/Algorithm

Behavioral/STAR

Technical Knowledge

Past Experience