• Lead a data science team and cross-functional projects • Innovate and improve machine learning models • Partner with business leaders and technical experts across the company • Develop new data sources and improve our modeling methodology • Apply models with sound risk management

• Partner directly with CX directors, managers, and executive leadership to deliver prescriptive, data-backed guidance for strategic planning. • Analyze customer health scores, product usage, and support trends to perform deep-dive retrospective analyses on churn and contraction drivers. • Design and execute impact measurement models that move past baseline usage metrics to quantify actual gross retention rate (GRR) improvements, net revenue retention (NRR) gains, and process efficiencies. • Lead the quantitative analysis for complex special projects, including annual account carves, territory balancing, and customer segmentation strategies. • Using Large Language Models (LLMs) to rapidly prototype scripts, automate ad-hoc reporting requests, and build lightweight data workflows. • Actively leverage the native AI components within Snowflake and our broader business intelligence stack to accelerate context gathering and surface predictive customer trends. • Map out how multi-source data flows between our primary platforms to create a unified, accurate view of the post-sales ecosystem. • Write high-performance, production-grade SQL queries directly within Snowflake to manipulate and model complex datasets. • Serve as part of the core CX liaison to the Enterprise Data & Analytics (ED&A) team, owning downstream data requirements and standardizing metric definitions.

• You will bring statistical rigor to business decisions. • Within the BI team, your mission is to go beyond descriptive analysis by applying statistical and machine learning models to find patterns, validate hypotheses, and generate forecasts that guide real strategies. • Day-to-day, you will model complex problems with Python, work with large volumes of data in ClickHouse and BigQuery, and collaborate with product and operations teams to ensure the models deliver real value. • Conduct statistical analyses to answer business questions: hypothesis testing, correlation analysis, segmentation, and predictive modeling; • Perform exploratory data analysis (EDA) to understand the data before modeling, identifying patterns and inconsistencies; • Write complex SQL queries in ClickHouse and BigQuery to extract and prepare data for analysis and modeling; • Use Python for data manipulation, exploratory analyses, and model prototyping; • Communicate results and insights clearly to business teams—translating statistics into decisions; • Collaborate with the BI team to define metrics, data quality standards, and analytical best practices; • Monitor models in production, tracking performance and proposing continuous improvements;

• Responsible for end-to-end delivery of data management services • Collaborate with internal and external customers • Ensure staff deliver high quality, timely service and meet all regulatory requirements • Hire, manage staff performance, utilization, retention, process improvements • Financial management for assigned projects