Senior Sales Analytics Strategist

Angi; Denver (CO); On-site; USD 115,000 - 205,000; Full time

Benefits offered by this job

Year-end bonus

Equity package

Medical, dental, vision

Flexible vacation

Pet discount plans

401K retirement plan

Job summary

Angi in the United States is seeking a Staff Analyst to join the Sales Analytics team as a senior individual contributor. You will design predictive models, improve prospect scoring, and optimize lead allocation to drive revenue and efficiency.

Collaborate with sales leadership, operations, and data engineering to build analytics pipelines, evaluate dial strategies, and present clear insights to executives.

Qualifications

• Bachelor's degree in a data-focused field, or equivalent experience.
• 8+ years of analytical experience in sales analytics or revenue operations.
• Strong SQL and data analysis skills; proficient in Python or R.
• Experience with data visualization tools (Tableau/Power BI/Looker).
• Hands-on predictive modeling experience (lead scoring, conversion probability).
• Proven ability to integrate AI tools into analytics workflows.

Responsibilities

• Improve prospect lead scoring models with conversion and revenue estimates.
• Optimize dial strategy to maximize rep time and outreach efficiency.
• Design territory alignment and lead allocation strategies.
• Build and maintain sales performance reporting across hierarchy levels.
• Conduct prospect database quality analysis and segmentation.
• Partner with data engineering to maintain automated scoring pipelines.
• Present findings and recommendations to sales executives.

Skills

Lead scoring

Predictive modeling

Sales analytics

SQL

Python/R

Data storytelling

Mentoring

Education

Bachelor's degree in Data Science, Economics, Statistics, Engineering

Master's degree preferred

Tools

SQL

Python

R

Tableau

Power BI

Looker

Job description

Angi in the United States is seeking a Staff Analyst to join the Sales Analytics team as a senior individual contributor. You will design predictive models, improve prospect scoring, and optimize lead allocation to drive revenue and efficiency.

Collaborate with sales leadership, operations, and data engineering to build analytics pipelines, evaluate dial strategies, and present clear insights to executives.