Staff Analyst, Commercial Analytics

Angi•Denver, CO

3d•$115,000 - $205,000

About The Position

We are seeking an experienced and data-driven Staff Analyst to join our Sales Analytics team as a senior individual contributor. This role will focus on optimizing the performance of our Sales Organization by building and maintaining the analytical systems that power how we score, prioritize, allocate, and contact prospects. You will work closely with sales leadership, operations leaders, and data engineering teams to design predictive models, evaluate dial strategies, and deliver actionable insights that directly drive revenue growth. As a key contributor, you will own the end-to-end analytics behind prospect scoring, territory alignment, lead allocation, and sales rep performance — translating complex data into decisions that move the business forward.

Requirements

Bachelor's degree in Data Science, Economics, Statistics, Engineering, or a related field (Master's degree preferred).
8+ years of analytical experience in a sales analytics, revenue operations, or B2B/B2C sales-adjacent environment; experience supporting an outbound sales or call center organization is a strong plus.
Strong proficiency in SQL as well as data analysis tools such as Python or R
Expertise in data visualization tools such as Tableau, Power BI, or Looker.
Hands-on experience building and deploying predictive models (conversion probability, lead scoring, propensity models) that directly inform sales rep workflows or CRM systems.
Proven track record of integrating AI tools (Claude, ChatGPT, Gemini, Cursor, Zapier) into your daily analytical workflow as a core productivity multiplier that meaningfully shortens time to insight.
Strong communication skills to present complex data to cross-functional teams and non-technical stakeholders.
Ability to manage multiple projects independently in a fast-paced environment.
Experience mentoring junior analysts; ability to document and scale analytical processes, models, and reporting so the team’s work is maintainable and transferable.

Responsibilities

Continuously improve our prospect lead scoring models, including conversion probability estimation, expected revenue modeling, and composite lead score generation ensuring scores accurately reflect prospect quality and are actionable for sales reps.
Analyze and optimize dial strategy including when to dial, how frequently to attempt contact, and resting strategy (when to temporarily pause outreach on a prospect) — using profitability and conversion data to maximize return on rep time and phone capacity.
Design and evaluate territory alignment and lead allocation strategies, including vertical-based routing (e.g., CHL vs. general floor), rep tier-based lead assignment, and Primary Work Category-level segmentation, ensuring the right prospects reach the right reps at the right time.
Build and maintain sales performance reporting across the full hierarchy from individual rep metrics (dials, dial penetration, dial saturation, submit conversion) up through manager and director views enabling leadership to quickly identify performance gaps and coaching opportunities.
Conduct prospect database quality analysis, including segmentation of the prospect pool by quality category (Good, Bad, Unsure), vertical assignment, and score-based profitability — informing headcount planning, dialing prioritization, and pipeline health.
Partner with data engineering to maintain and evolve the automated pipelines that generate daily prospect scores, distribute scored prospects to the sales floor, and replicate scoring data into downstream CRM and sales systems.
Present analytical findings and strategic recommendations directly to sales executives and operations leaders, translating model outputs and data into clear narratives that drive decisions on rep headcount, prospect mix, and outreach strategy.
Continuously evaluate model performance and iterate on scoring methodology — incorporating new feature signals (e.g., enrichment data, transcript features, affiliate/source encoding) and improving model explainability so sales reps and leaders understand why a prospect scores the way it does.
Leverage AI tools (e.g., Claude, ChatGPT, Cursor, Gemini) to accelerate the analytical workflow — from faster hypothesis generation and code authoring to synthesizing large volumes of sales data into actionable insights with greater speed and precision.
Automate repetitive analytical tasks — data pulls, report refreshes, QA, and ad hoc summarization — using AI-assisted scripting and workflow tools to maximize time spent on high-value analysis.