Manager

Overview

In this data scientist role, you will transform telemetry from a mobile app platform into decision-ready dashboards and insights. You’ll work within a four-layer ingestion-analysis-S3-storage-visualization architecture to support TLS leadership. You’ll build Streamlit dashboards, integrate diverse data sources, and deliver quantitative analyses that inform product and platform decisions. This is a hands-on, end-to-end role with cross-functional collaboration and a strong focus on scalable, architecture-driven analytics.

Responsibilities

• Transform raw telemetry into actionable insights and dashboards
• Develop Streamlit dashboards with multi-page layouts and session state
• Integrate data from Snowflake, OpenSearch, REST sources, and other systems via API/SQL
• Perform data transformation and time-series analyses using pandas, NumPy
• Create visualizations with Plotly, matplotlib, and seaborn
• Work with AWS services (S3, Parquet) and containerized deployments (Docker, Kubernetes)
• Participate in CI/CD processes and testing (pytest)
• Communicate data-driven findings to leadership and cross-functional teams
• Own end-to-end feature delivery from data source to visualization
• Contribute to Architecture Decision Records and maintain clean architecture

Key requirements

• Strong Python 3.11+ experience
• Pandas and NumPy for data transformation and time-series work
• Streamlit dashboard development (multi-page, session state)
• API/SQL data integration (Snowflake, OpenSearch, REST sources)
• Data visualization using Plotly, matplotlib, seaborn
• AWS experience (S3, Parquet) and Docker, Kubernetes
• CI/CD and testing with pytest
• Applied statistics for anomaly detection (rolling median, MAD, z-score)
• Time-series thinking for frequency-aware baselining
• Understanding of mobile app KPIs and store metrics (iOS/Android)
• Ability to translate leadership questions into metrics and views
• Senior-level ownership within a layered architecture

• Clear communication of data-driven findings to leadership
• Cross-functional collaboration with QE, delivery, and product teams
• Documentation habits
• Python 3.11+
• pandas, NumPy
• Streamlit

…