Senior Revenue Forecasting Analyst

AmSpec Group LLC; Pasadena (TX); On-site; USD 90,000 - 130,000; Full time

Job summary

AmSpec Group LLC seeks a Senior Analyst to own and improve revenue and cost forecasting models. You will work with large datasets to produce projections guiding business decisions and partner with leadership to translate analysis into actionable recommendations.

Responsibilities include cleaning data from ERP systems, maintaining forecasting models, and creating dashboards for non-technical stakeholders. Strong skills in Python, SQL, and Excel are essential, as is the ability to document data

Qualifications

• Bachelor’s degree in data science, statistics, economics, finance, CS, mathematics, or related field (or equivalent experience).
• 4–6 years of experience in data analysis.
• Proficiency in Python (pandas) or R.
• Solid SQL skills (joins, aggregations, window functions).
• Strong Excel skills with formulas, pivot tables, and scenario modeling.
• Strong understanding of statistics (variance, regression).
• Comfort with large datasets and attention to detail; clear written communication.

Responsibilities

• Clean, validate, and transform large datasets from ERP and accounting systems for analysis.
• Own and maintain revenue and cost forecasting models.
• Create reports and dashboards that present results clearly to non-technical stakeholders.
• Document data sources, assumptions, and model logic to ensure repeatability.
• Flag data quality issues and work to improve data pipelines.

Skills

Python (pandas)

SQL

Excel

Statistics

Data transformation

Documentation

Communication

Education

Bachelor’s degree

Tools

Power BI

Tableau

Looker

Git

Job description

AmSpec Group LLC seeks a Senior Analyst to own and improve revenue and cost forecasting models. You will work with large datasets to produce projections guiding business decisions and partner with leadership to translate analysis into actionable recommendations.

Responsibilities include cleaning data from ERP systems, maintaining forecasting models, and creating dashboards for non-technical stakeholders. Strong skills in Python, SQL, and Excel are essential, as is the ability to document data