IntePros
Overview Data Analyst I – Geospatial & Competitive Insights
We are seeking a Data Analyst to perform geospatial and competitive bid analysis, providing insights that inform strategic decision-making. This role involves analyzing bid locations, creating summary statistics, and developing dashboards to track performance metrics. You will work with geospatial datasets, automation scripts, and state-specific formatting requirements to produce accurate, actionable outputs for the business.
Responsibilities Conduct map-based analysis to inform bidding strategies, including data review, Python scripting, and statistical summaries.
Analyze locations bid and won, including competitive bid trends and insights.
Combine geospatial data with reference tables to create meaningful, actionable reports.
Design and maintain dashboards/visualizations for BEAD location statistics.
Generate specification files using automated scripts, ensuring compliance with state-required formatting standards.
Top Required Skills Analytical & Modeling Skills – Ability to perform data analysis, create forecasts, and solve business problems using structured approaches.
Python – Basic scripting for automation, data transformation, and analysis.
Excel – Proficiency in advanced formulas, pivot tables, and data organization.
Skills & Experience Required Undergraduate degree in business, finance, engineering, or a related field (Graduate degree preferred).
0–3 years of experience in data analysis, business forecasting, or a related role.
Experience in building and managing financial models for forecasting and variance analysis.
Basic Python knowledge; SQL experience preferred.
Strong written and verbal communication skills.
Highly detail-oriented, with the ability to prioritize and adapt in a dynamic environment.
Work Environment & Structure Collaborative team environment with opportunities to work independently on analytical projects.
Mix of technical analysis, reporting, and stakeholder communication.
Exposure to high-impact strategic initiatives through data-driven decision-making.
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