Pricing Analyst Job ID 2026-1959

Internet Brands•El Segundo, CA

2d•$100,000•Onsite

About The Position

The Pricing Analyst will be the analytical engine behind the company's monetization strategy. This role involves partnering closely with Product, Sales, Marketing, and Finance to optimize pricing and packaging, drive revenue growth, and improve customer retention. The analyst will be expected to leverage modern AI tools to accelerate data analysis, build smarter models, and translate complex insights into actionable business strategies.

Requirements

2–5 years of experience in pricing strategy, corporate finance, revenue operations, management consulting, or data analytics—ideally within a B2B SaaS or subscription software environment.
Advanced proficiency in data modeling. Ability to build complex financial models, cohort analyses, and sensitivity scenarios. Ability to create and optimize price elasticity of demand models (PED) across products, bundles and customer segments.
Establish dynamic pricing strategies, discount structures, and promotional calendars to maximize revenue or margin targets.
Strong proficiency in SQL to pull, clean, and manipulate large datasets.
Experience with BI/Data Visualization tools (e.g., Tableau, Looker, PowerBI) is required.
Demonstrated ability to integrate AI assistants (e.g., ChatGPT, Claude, Gemini, GitHub Copilot) into your daily workflow to write/debug SQL, summarize research, or accelerate financial modeling.
Deep understanding of subscription pricing, unit economics, and standard metrics (CAC, LTV, NRR, MRR).
Ability to translate complex data and modeling into clear, executive-level presentations (PowerPoint/Keynote) and actionable business recommendations.
Proven ability to manage multiple projects simultaneously, work autonomously, and thrive in a fast-paced environment.

Nice To Haves

Degree in Finance, Economics, Statistics, Mathematics, or a related quantitative field.
Experience with statistical programming (Python or R) for advanced data analysis or price elasticity modeling.
Familiarity with applying Machine Learning (ML) concepts to pricing challenges (e.g., predictive churn modeling, dynamic pricing algorithms, or automated segmentation).
Familiarity with billing and CRM systems (Salesforce)
Direct experience running pricing experiments

Responsibilities

Analyze tier structures, feature allocation, and add-on pricing to optimize value capture across customer segments.
Build quantitative models to forecast the revenue impact of price changes, promotional discounts, packaging adjustments, and plan migrations.
Leverage generative AI and predictive analytics tools to accelerate data wrangling, automate repetitive reporting workflows, and uncover deeper behavioral trends in large datasets.
Track and analyze key subscription metrics—including MRR/ARR, Churn, Net Retention Rate (NRR), LTV, Customer Acquisition Cost (CAC), and ARPU.
Design, monitor, and evaluate monetization experiments, price sensitivity tests, and promotional strategy rollouts.
Benchmark competitive pricing models, packaging strategies, and monetization trends across the industry, utilizing AI to rapidly synthesize market intelligence.
Serve as a strategic partner to Product Management and Sales Leadership to ensure pricing strategies are competitive, easily understood by customers, and operationally viable to execute.