Lead Data Analyst

pureIntegration•Reston, VA

1d•$60 - $75•Remote

About The Position

We are seeking a Lead Data Analyst to lead a high-impact analytics team focused on network reliability and subscriber experience across approximately 30 million customers. This role is ideal for a senior analyst who operates at a near–Data Scientist level, combining deep analytical rigor, causal reasoning, and hypothesis-driven problem solving with strong communication and team leadership. This position goes well beyond standard reporting. The person in this role will be expected to answer complex business and operational questions such as: What happened? Why did it happen? What should we do about it? The ideal candidate will serve as both a hands-on technical lead and a team lead, guiding analysis, delegating work, and partnering closely with business and technical stakeholders. This is a highly visible, customer-facing role that may require travel and on-site presence as needed. This position is fully remote within the U.S. and will be a W-2 hourly engagement for 6 to 9 months. The hourly range is $60/hr - $75/hr. Candidates will be paid based on their work experience and skills. Candidates are also eligible for limited benefits such as health insurance, professional development, training, our referral bonus program, and our wellness program.

Requirements

7–10+ years of experience in data analysis, advanced analytics, data science, or a related field.
Bachelor’s degree in Engineering, Computer Science, Statistics, Mathematics, Information Systems, or a related discipline, or equivalent professional experience.
Expert-level proficiency in SQL, including the ability to write queries on the fly, work with large datasets, and structure efficient, analytically sound logic.
Expert-level proficiency in Excel, including advanced formulas, pivot tables, data modeling, reconciliations, and large dataset analysis.
Strong working proficiency in Tableau and MicroStrategy.
Python is required at a minimum for the ability to read, understand, and debug existing code. Ability to write Python scripts independently is preferred.
Strong understanding of analytical fundamentals, including aggregation logic, metric design, weighted averages, ratios, frequencies, and rates.
Demonstrated strength in causal reasoning and observational data analysis, including the ability to distinguish correlation from likely causation and to structure defensible analytical conclusions.
Experience working with extremely large datasets and translating complex data into clear business insights.
Strong written and verbal communication skills, including the ability to present complex findings clearly to both technical and non-technical audiences.
Demonstrated leadership experience, including delegating work, reviewing output, guiding analysts, and managing delivery expectations.
Strong organizational skills and the ability to manage multiple priorities in a fast-paced environment.

Nice To Haves

Experience working in telecom, cable, broadband, video, DOCSIS, or network operations environments.
Experience with AWS / Amazon Redshift and cloud-based analytical workflows.
Experience with machine learning modeling is a plus.
Familiarity with other business intelligence and visualization tools such as Power BI, Looker, or similar platforms.
Experience supporting operational, technical, or reliability-focused analytics teams.

Responsibilities

Lead complex analytical investigations into service reliability, subscriber support-seeking behavior, and network performance trends.
Perform deep-dive analysis across large-scale datasets, including subscriber-level data with daily granularity and very large aggregate tables.
Apply causal inference and hypothesis-driven analysis to observational data in order to identify likely drivers of trends, degradations, and performance changes.
Use segmentation, drill-through analysis, before/after comparisons, and control-group logic to isolate likely causes and recommend next actions.
Write and execute advanced SQL queries in Amazon Redshift, including complex joins, aggregations, and large-scale data manipulation.
Use Excel as a primary analytical tool, including pivot tables, advanced formulas, aggregations, reconciliation techniques, and structured analytical modeling.
Build and interpret visualizations and dashboards using Tableau and MicroStrategy, and demonstrate familiarity with other major visualization tools as needed.
Read and debug Python code used in analytical workflows, validations, or lightweight automation. Ability to write scripts from scratch is preferred but not required.
Demonstrate an AI-enabled analytical mindset by identifying opportunities to use AI tools to accelerate analysis, improve insight generation, and strengthen communication of findings.
Prepare polished, executive-ready deliverables in PowerPoint, email summaries, and supporting documentation, with strong attention to clarity, logic, and audience-appropriate messaging.
Lead and supervise a small team of analysts, including mid-level and junior resources responsible for structured analysis, validation, and reconciliation activities.
Delegate work effectively, establish quality checks, and ensure consistent, accurate, and timely delivery across the team.
Partner with technical leadership, operations teams, and subject matter experts to rapidly understand domain context and translate data into actionable recommendations.
Develop a working knowledge of network architecture, DOCSIS, cable/video/internet service concepts, and related operational processes in order to interpret results more effectively.
Ensure that all metrics and outputs are analytically sound, including proper use of averages, weighted averages, rates, ratios, and other aggregation methods.