ServiceNow's Customer Service & Support (CSS) team needs to operationalize predictive models, design rigorous experiments, and translate insights into clear, actionable recommendations for executives to treat data as a critical business asset—reliable, secure, compliant, and readily available to drive decision-making, innovation, and growth.
Requirements
- Proficiency in SQL and Python; experience building analyses or simple models.
- Familiarity with experimentation concepts (A/B testing, control/holdout design).
- Strong foundation in statistics and data analysis methods.
- Experience with data visualization tools (Tableau, Power BI, Plotly, or equivalent).
- Nice to have: exposure to cloud data platforms (Snowflake, Databricks, AWS, GCP, or Azure), AI/ML basics, or support/customer success analytics.
Responsibilities
- Support the development of forecasts (volume, time-to-resolution) and basic uplift/propensity models.
- Assist in designing and analyzing A/B and holdout tests; summarize impact for key stakeholders.
- Build driver analyses and scenario models with guidance from senior team members.
- Write clean SQL and Python code to build data pipelines and analysis workflows.
- Document methodologies and ensure Responsible AI practices are followed.
- Create clear, concise visualizations and presentations for business audiences.
- Monitor model and forecast performance, highlighting issues or opportunities.
Other
- Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving.
- Strong communication skills with the ability to translate data into actionable insights.
- Partner with cross-functional teams to translate insights into recommendations.
- Stay current on trends in predictive analytics and experimentation, sharing learnings with the team.
- 2+ years of experience in data science, analytics, or a related field.
