Senior Analyst, Data T500-22350

Position: Senior Analyst, Data [T500-22350]
About T-Mobile:
T-Mobile US, Inc. (NASDAQ: TMUS), headquartered in Bellevue, Washington, is America’s supercharged Un-carrier, connecting millions through its strong nationwide network and flagship brands, T-Mobile and Metro by T-Mobile. Customers benefit from an unmatched combination of value, quality, and exceptional service experience.

About TMUS Global Solutions:
TMUS Global Solutions is a world-class technology powerhouse accelerating the company’s global digital transformation. With a culture built on growth, inclusivity, and global collaboration, the teams here drive innovation at scale, powered by bold thinking.
TMUS India Private Limited operates as TMUS Global Solutions.

Sr Analyst, Data – Consumer Customer Success (L08)

About the Role:

The Senior Analyst, Data plays a pivotal role in delivering high-impact data analysis, SQL-driven insights, and operational intelligence that inform strategic and tactical decisions across T-Mobile’s Digital and Omnichannel businesses.
This role drives the analysis of sophisticated business challenges, assesses system and data implications, and develops efficient analytical solutions—including gap and process analysis. The analyst defines data requirements, generates actionable insights, and collaborates with business collaborators to shape strategy and optimize outcomes.
Employing advanced SQL, Python, Adobe Analytics, and cloud-based data platforms, the Senior Analyst performs investigative analyses across digital, retail, care, chat, and other customer touchpoints. They compose dashboards, reports, and customer journey insights that improve digital experience, evaluate funnel performance, and guide optimization initiatives. Responsibilities also include ensuring data integrity through quality validation, anomaly detection, and root cause analysis.
Partnering closely with digital product marketing, Mar Tech, data engineering, and analytics teams, this role defines scalable data solutions, supports A/B testing, and applies new technologies such as machine learning and large language models (LLMs) to accelerate insight generation. The analyst translates business questions into clear analytical approaches and delivers data-driven recommendations that drive enterprise-wide impact.

What You’ll Do:

Data Analysis & Insights:
Use SQL and Python to analyze omnichannel data (web, app, retail, care, chat, etc.) to identify trends, friction points, and performance drivers.
Generate actionable insights and recommendations that inform business decisions.
Develop and evaluate A/B tests, including variance and lift analyses.
Leverage tools such as Databricks, Snowflake, Big Query, Adobe/CJA, and Quantum Metric.

Requirements & Customer Alignment:
Gather, clarify, and align analytics requirements with business and digital objectives.
Translate business questions into structured analytical solutions, data models, or dashboards.
Partner multi-functionally to endasure scalability and alignment with critical metrics.

Dashboarding & Reporting:
Build and maintain dashboards in Tableau, Power BI, or Looker.
Define and operationalize clear benchmarks.
Ensure reporting is accurate, timely, and aligned with business needs.

Data Quality & Troubleshooting:
Validate data across platforms (Azure, GCP, AWS, Snowflake).
Detect anomalies, debug issues, and perform root cause analyses.
Collaborate with engineering teams to ensure accurate tagging and durable fixes.

Documentation & Modeling:
Develop data models, tracking specifications, and analytics documentation.
Clearly document data logic, assumptions, and methodologies to support cross-team understanding.

Planning & Teamwork:
Handle timelines and deliverables with autonomy.
Provide progress updates and support analytics roadmap development, including ML/LLM initiatives.

Process Improvement:
Improve data quality, automation, and analytics workflows.
Promote guidelines for reproducibility, documentation, and version control (e.g., Git Lab).

What You’ll Bring :
Bachelor's Degree (Required) - plus 7 years of related work experience OR Advanced degree with 3 years of related experience. Academic background in quantitative, technical, or analytical fields preferred.
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