Analyst II, Full Stack (Customer Servicing Analytics)

About This RoleAI processing…

Key Responsibilities

• 1
  Planning: Own planning and staffing for UK and new-geography launches and special teams. Develop and maintain the guardrail metrics.
• 2
  Foundations: Build working familiarity with the underlying data, including demand signals, agent rosters (team, title, country), and agent activity (delivered hours, status), and license demand.
• 3
  Infrastructure forecasts: Own demand forecasts for checkouts and app opens in CA and UK and new geographies.
• 4
  Report on forecast health for UK, CA, and other geos (accuracy and outlook).
• 5
  Advise Customer Operations real-time management (UK) on agent productivity.
• 6
  Curate AI knowledge for Customer Operations (UK) and UK Infrastructure forecasting.
• 7
  Build and maintain forecasting models, using time series, regression, and machine learning, to support contact forecasting, headcount and license planning, and budgeting.
• 8
  Partner with stakeholders to frame planning and forecasting problems, develop supporting metrics and diagnostics, and support high-quality decisions.
• 9
  Surface productivity and efficiency improvements using budget and financial performance data.
• 10
  Present recommendations to leadership, drive timely decisions, and communicate clearly with cross-functional partners.
• 11
  Partner with operational planning and other analytics teams to understand the business context for headcount and workforce scheduling, and get the data needed for accurate forecasts.
• 12
  Stay current on the business and our changing technical environment.

Requirements

• Bachelor's, Master's, or PhD in a quantitative field (e.g., statistics, industrial engineering, operations research) and 5+ years solving forecasting, planning, or related quantitative problems.
• Strong proficiency in SQL and Python or R, and hands-on experience with a modern cloud-native data platform (e.g., Databricks, Snowflake, BigQuery, or equivalent).
• Hands-on experience using AI/LLM tooling across the analytics workflow: writing, validating, and iterating on AI-generated SQL and Python, and integrating AI outputs into analyses that stakeholders trust.
• Experience building optimization models using linear programming techniques (e.g., CPLEX, Gurobi) is a plus.
• Strong experience developing and validating statistical forecasting models, with disciplined approaches to performance measurement, backtesting, and robust error tracking.
• Proven ability to independently structure ambiguous problems and select the appropriate analytical approach without predefined direction.
• Clear, persuasive communicator with strong stakeholder management skills and the ability to influence senior leaders across technical and non-technical audiences.
• Strong bias toward automation: treat repetitive manual work as avoidable drudgery and build durable, automated systems, delegating to machines what they can do more reliably and efficiently than humans.
• High standards of humility, honesty, and ownership: you take responsibility for outcomes, invest in your own growth, and actively develop others.

Perks & Benefits