Lead Data Analyst / Advanced Analytics Lead

Forged Fiber 37•Dallas, TX

2d•Hybrid

About The Position

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.

Requirements

5+ years of progressive experience in data analysis, business analytics, advanced analytics, or a related field
Demonstrated ability to manage complex datasets across multiple sources and repositories, including data cleansing, mapping, and discrepancy resolution
Strong statistical and analytical skills with experience developing and validating models for decision support
Advanced SQL skills and experience building dashboards/visualizations
Ability to communicate insights clearly and influence stakeholders with data-driven recommendations
Strong planning and prioritization skills with the ability to manage competing demands and consistently deliver high-quality results on time.
Self-directed and resourceful, with the ability to operate effectively with limited guidance while maintaining alignment with business priorities and stakeholder expectations.

Nice To Haves

Bachelor’s degree (BS/BA) in Computer Science, Mathematics, Statistics, Economics, Engineering, or a related field (or equivalent experience)
Experience with data warehouse/lake architectures and platforms (e.g., Snowflake, Databricks)
Relevant certifications (tool-, cloud-, or analytics-focused), as required/appropriate in some areas

Responsibilities

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.
Lead significant analytics initiatives with autonomy, coordinating across teams as needed to deliver results.
Operate independently, using sound judgment to define the path forward, remove barriers, and keep work progressing toward expected outcomes.
Manage multiple priorities, develop clear workplans, and proactively coordinate timelines, dependencies, and stakeholder expectations to deliver accurate, timely results.
Use a range of analytics and visualization tools and other modern analytics platforms as applicable.
Leverage cloud and big data ecosystems based on project needs and environment.
Serve as a subject matter expert and mentor to less experienced analysts; provide guidance on methods, tooling, storytelling, and quality standards.
Contribute to long-term analytics capabilities through standards, templates, reusable code, and continuous improvement of processes.