Turns raw telemetry into decision-ready insights (not deep ML, but solid quantitative reasoning)
Understands mobile app Kis across Bookings, Adoption, Engagement, App Health, Card Member Voice, Quality Engineering
Be familiar with iOS/Android store metrics, crash/stability, QE/regression concepts
Translates leadership questions into metrics and views
Provide senior-level ownership within an established layered architecture; respects design principles (no business logic in Ul, filter-agnostic analysis)
Contribute to and follows Architecture Decision Records (ADRs)
Own features end-to‑end: data source → analysis → dashboard
Communicates data-driven findings clearly to leadership and non‑technical stakeholders
Works cross‑functionally with QE, delivery, and product teams
You will need experience working with:
Strong Python 3.11+, pandas, NumPy for data transformation and time-series work
Streamlit dashboard development (multi-page, session state, query-param nav)
API/SQL data integration (Snowflake, OpenSearch, REST sources)
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