Lead Data Analyst - Dallas, TX

About Forged Fiber

At Forged Fiber, our mission is bold but simple: deliver fast, reliable, future-proof connectivity that builds the foundation for everything online. As we execute, we believe the right way to do something is the only way. This foundation guides how the company builds, operates, and maintains a state-of-the-art open-access fiber network platform that empowers millions.

Forged Fiber is about more than building a network. It is about people. Every role matters. Every contribution counts. Together, employees create impact through teamwork, trust, and a shared commitment to excellence.

The Lead Data Analyst / Advanced Analytics Lead researches, collects, processes, and organizes data from multiple internal and external sources to deliver trusted reporting, actionable insights, and advanced analytical solutions. This role owns key elements of the data lifecycle—data ingestion, cleansing, mapping, quality control, and discrepancy resolution—and serves as the owner of the most accurate, reliable data across various platforms and tooling, while also applying advanced statistical methods and predictive modeling to solve complex business problems.

The role partners with stakeholders to translate business questions into analytical approaches, creates insights that drive better business decisions and operational efficiencies, builds compelling visualizations and decision-support tools, and influences strategy through insight-driven recommendations.

Work Location Dallas/Hybrid

• Gather, preprocess, cleanse, and validate data from diverse sources (e.g., operational systems, external datasets, data lakes/warehouses) to ensure accuracy, completeness, and readiness for analysis.
• Manage complex data movement and storage across multiple repositories; maintain and update interfaces as needed.
• Define and maintain data rules, transformations, and mapping documentation to support consistent and reliable data use across platforms.
• Own the accuracy, consistency, and reliability of data across multiple business platforms, repositories, dashboards, and analytics tools.

• Work with relational and warehouse technologies to support scalable analytics.

• Identify, reconcile, and resolve data discrepancies across business applications and reporting layers; perform root‑cause analysis and drive corrective actions.
• Implement quality assurance practices including auditing, reconciliation, and control checks to ensure data integrity and reliability.
• Establish and maintain repeatable processes and documentation that improve consistency, transparency, and auditability of analytics outputs.

• Analyze and interpret complex datasets to identify trends, relationships, and drivers of business outcomes.
• Apply advanced statistical methods to quantify variance, evaluate hypotheses, and support decision-making.
• Build, test, and validate predictive models and evaluate performance in real‑world conditions.
• Identify causal relationships, trigger points, and predictive signals to support proactive business actions.

• Develop clear, precise, and compelling dashboards, reports, and visualizations that communicate findings to technical and non‑technical audiences.
• Translate analytical results into actionable recommendations, highlighting business implications, tradeoffs, and opportunities.
• Respond to business requests with structured analysis, ensuring stakeholder alignment on definitions, assumptions, and success measures.

• Create insights that identify efficiency opportunities, improve decision quality, and help leaders prioritize actions that deliver measurable business value.

• Develop business cases and complex analytical models to evaluate process changes, financial impacts, business model improvements, and performance optimization opportunities.
• Influence decision‑making by providing executive‑ready insights, scenario analyses, and recommendations tied to measurable outcomes.
• Le…