Purpose of Job
The Senior Analyst, Analytics & Insights is responsible for delivering high‑impact analytics, insights, and experimentation support across Customer Contact Center operations (including Care Pod initiatives) and Marketing Science.
The incumbent operates with a high degree of autonomy within defined problem spaces, translating business questions into several types of data products like structured analysis, dashboards, data science models.
Partnering closely with stakeholders to inform decisions, this role works alongside Data Science teams (internal and external) to ensure analytical outputs are measurable, interpretable, and actionable.
This is a hands‑on individual contributor role requiring strong analytical judgment, technical proficiency (SQL, Power BI, Python), and the ability to clearly communicate insights to both operational and growth stakeholders.
Main Activities
Customer Contact Center & Care Pod Analytics (70%)
Deliver analytics and insights for Contact Center performance (SLA, volumes, handle time, repeat contact, channel mix).
Build and maintain executive-ready Power BI dashboards and scorecards focused on clarity and decision-making.
Conduct root-cause analysis on call/chat drivers using structured and transcript data.
Partner with Contact Center leadership and Workforce Management on planning, performance, and operational decisions.
Support Care Pod initiatives (chatbots, routing, agent assist) with experimentation, rollout measurement, and impact analysis.
Translate prototypes (e.g., Figma) into production-grade analytics solutions, including data modeling and DAX optimization.
Act as an AI analytics partner, defining KPIs, monitoring adoption, and embedding insights into workflows.
Marketing Science & Growth Analytics (30%)
Support analytics across acquisition, onboarding, and lifecycle marketing.
Design and analyze A/B and multivariate experiments.
Build customer cohorts to evaluate campaign performance, retention, and engagement.
Develop dashboards and insights to track marketing performance and identify growth opportunities.
Translate findings into actionable recommendations for targeting, channel strategy, and prioritization.
Qualifications
3–5 years in analytics, BI, or data-driven roles (financial services is an asset).
Strong SQL and Power BI (data modeling, DAX, dashboard design).
Experience with experimentation (A/B testing) and cohort analysis.
Proficiency in Python for statistical or analytical work.
Ability to analyze structured and unstructured data (e.g., transcripts, NLP tools).
Strong stakeholder management with ability to translate data into business insights.
Comfortable working cross-functionally (Operations, Marketing, Product, Data Science).
