Senior Manager, Analytics (Customer Care)

Angi•Denver, CO

4d•$155,000 - $210,000•Hybrid

About The Position

Angi’s Care Analytics team is at the center of how we understand, grow, and retain our Pro network. The Senior Manager, Analytics stewards the analytical strategy and cadence that drives decision-making across Pro retention, churn, cash collection, and care team effectiveness. In this role you will serve as the primary analytical partner to our customer care business unit —translating complex, weekly data signals into actionable narratives. You will lead a team of analysts, manage a dynamic project backlog, and set the standard for analytical rigor across Customer Care Network metrics. This is a highly visible, high-impact role that requires someone equally comfortable writing SQL one day and presenting findings to a leadership team the next morning.

Requirements

6+ years of analytics experience, with 2+ years managing analysts in a fast-paced, data-intensive environment.
Proven track record stewarding executive-facing reporting cadences—ideally weekly business reviews—with a strong ability to translate metric movements into business narratives.
Expert-level SQL and proficiency with BI tools (Looker preferred); comfortable building and validating complex metric logic from scratch.
Experience with retention/cohort analysis, churn modeling, or marketplace analytics.
Strong statistical judgment: ability to distinguish meaningful trends from noise, apply regression analysis, and design structured investigations with clear hypotheses.
Exceptional written and verbal communication—able to write tight, stakeholder-ready commentary (with appropriate caveats) under time pressure.
Demonstrated ability to manage a dynamic project backlog, negotiate priorities with multiple stakeholders, and deliver on competing timelines.
AI first mentality who leverages any tool available to increase efficiency, accuracy, and quality of insight generation.

Nice To Haves

Experience in a marketplace, e-commerce, or home services business with a two-sided network (pro/consumer or seller/buyer).
Familiarity with Salesforce data structures and CRM-based analytics (save events, churn events, case history).
Experience with metric migration projects (e.g., moving reporting between data warehouses or unified explore environments).
Working knowledge of A/B testing and holdout experiment design.
Exposure to AI/ML applications in analytics (coaching impact sizing, predictive churn, prospect scoring).
Jira or similar project tracking experience for managing analytical work intake.

Responsibilities

Steward and publish weekly business reviews, synthesizing key metrics and signals into clear, stakeholder-ready commentary.
Flag material metric movements proactively—distinguishing noise from signal—and recommend whether to investigate immediately, monitor, or backlog.
Lead the Weekly Metrics review for senior leadership, including narrative development and proactive identification of metric gaps in our retention trends.
Manage transitions of report stewardship within the team and ensure analytical continuity (e.g., onboarding new analysts to weekly cadences without degrading output quality).
Run a weekly Care Analytics prioritization process: maintain the backlog across multiple stakeholder groups (Care leadership, Pro product, Finance), arbitrate competing priorities, and communicate trade-offs clearly.
Manage and develop a team of analysts (Senior Analysts, Analysts), providing coaching on both technical craft and business communication.
Define project scopes and ETAs, track delivery, and surface blockers early—including upstream data/engineering dependencies.
Champion the Analytics + AI literacy initiative, helping team members build skills in AI-assisted analysis and productivity tooling.
Drive structured investigations into metric deterioration Leverage regression analysis, cohort segmentation, and hypothesis testing to isolate drivers of key metrics and distinguish correlation from causation.
Partner with Data Science and Product Analytics on metric definitions, unified views for migrations, and new metric builds.
Validate and QA metric definitions end-to-end, including numerator/denominator alignment, data source mapping, and appropriate use of segment filters.
Act as the analytical voice in leadership discussions on customer metrics, rules, program effectiveness, and optimization strategies.
Translate ambiguous asks from business leaders into structured analytical plans with defined hypotheses, recommended cuts, and timelines.
Collaborate cross-functionally with Care Ops, Finance, Product, and Data Engineering to ensure analytical outputs are grounded in operational reality.
Partner with Data Engineering on data quality issues to ensure reporting reliability.