Lead Advanced Analytics

time left to apply End Date:
September 10, 2026 (6 days left to apply)

job requisition  R-119443

This position requires office presence of a minimum of 5 days per week and is only located in the location(s) posted. No relocation is offered.

The Lead Advanced Analytics role will be focused on advancing strategic wireline pricing through analytics, modeling, and data-driven insights that support the continued evolution of algorithm-based pricing. The position will help move the business forward by identifying pricing opportunities, validating model performance, performing deep-dive analysis across complex data sets, and translating findings into actionable recommendations that improve revenue, margin, and overall pricing effectiveness.

Key Roles and Responsibilities: Typical tasks may include, but are not limited to, the following:

Data Analysis and Interpretation: Gather, analyze, and interpret diverse data sets to solve a variety of business problems, predict behaviors, and identify causal relationships, trigger points, and predictions. Well-versed with Relational (Ex
- Oracle or MySQL) and/or Data Warehouse data storage (Ex
- Snowflake or Databricks Delta Lake). Data sources including but not limited to internal and external sources, datalakes, data warehouses such as eCDW, BIDW, etc.

Statistical Methods and Decision Support: Apply a range of advanced statistical methods to quantify data variances and uses traditional modeling techniques to support decision-making. Most common tools are Tableau, Palantir, PowerBI (AI Insights), Databricks, AWS Azure, Synapse, H2O Driverless AI, etc.

Business Case Development and Analytics Tools: Develop business cases and create complex models utilizing big data analytics tools (Ex
- Tableau, Power BI AI Insights, Databricks) for modeling and process integration, and to make recommendations for improvements to processes, financials, business models, etc. Build and test predictive models on various data samples and verifies their accuracy in real-world scenarios (Ex
- Linear/Logistic Regression, Time Series).

Reporting and Business Insights: Develop visualizations such as dashboards, reports and charts, and advise business partners on data patterns and relationships to recommend strategic directions. Advise business partners with regard to patterns and relationships in data to recommend business direction or outcomes.

Education/

Experience:

Bachelor’s degree (BS/BA) desired from an accredited University in a Quantitative field of study such as Data Science, Math, Statistics, Engineering or Physics.

Experience with the following: snowflake, SQL and Tableau/PowerBI, statistical analytics, executive communications, financial acumen and business case development.

Prior pricing experience is a plus.

5+ years of related experience.

This position requires office presence of a minimum of 5 days per week and is only located in the location(s) posted. No relocation is offered.

The Lead Advanced Analytics role will be focused on advancing strategic wireline pricing through analytics, modeling, and data-driven insights that support the continued evolution of algorithm-based pricing. The position will help move the business forward by identifying pricing opportunities, validating model performance, performing deep-dive analysis across complex data sets, and translating findings into actionable recommendations that improve revenue, margin, and overall pricing effectiveness.

Key Roles and Responsibilities: Typical tasks may include, but are not limited to, the following:

• Data Analysis and Interpretation: Gather, analyze, and interpret diverse data sets to solve a variety of business problems, predict behaviors, and identify causal relationships, trigger points, and predictions. Well-versed with Relational (Ex
  - Oracle or MySQL) and/or Data Warehouse data storage (Ex
  - Snowflake or Databricks Delta Lake). Data sources including but not limited to internal and external sources, datalakes, data warehouses such as eCDW, BIDW, etc.

• Statistical Methods and Decision Support: Apply a range of advanced statistical methods to quantify data variances and uses traditional modeling techniques to support…