Director, Analytics - B2B Growth

Snap Finance•West Valley City, UT

About The Position

Join the Consumer Growth Analytics team at Snap, where we leverage data to accelerate revenue and partner growth across the business. We’re seeking a senior leader to own analytics for a broad range of revenue-driving teams—including SMB Sales, Large Market Sales, Strategic Partnerships, Sales Ops, Rev Ops, and B2B Marketing. In this high-impact role, you’ll lead forecasting, opportunity sizing, and partner performance analysis; support enterprise deal development with market intelligence and RFP analytics; and improve lead qualification and onboarding efficiency to better serve our core ALICE customer (Asset Limited, Income Constrained, Employed). This is a strategic, cross-functional role on a collaborative, high-ownership team where innovative thinking, partnership, and measurable impact are the standard.

Requirements

10+ years of experience in analytics, strategy, or growth roles within B2B, fintech, or financial services environments, with demonstrated success across both enterprise and SMB sales models.
Proven ability to generate revenue impact through analytics in sales, marketing, and partner growth contexts.
Deep experience supporting enterprise partnership development—including forecasting, RFP response analytics, and market research.
Strong understanding of lead qualification, funnel conversion, and lifecycle management in SMB contexts.
Expertise in SQL and familiarity with Python or R for analytics and predictive modeling; ability to partner effectively with Data Engineering and Data Science teams.
Experience conducting web scraping and third-party data acquisition for market intelligence and strategic research.
Proficiency with modern analytics tools (e.g., Snowflake, dbt, Tableau, Looker, Amplitude).
Excellent storytelling, communication, and executive influence skills; capable of turning complex data into business-aligned insights.
Bachelor’s degree in a quantitative field (e.g., Statistics, Economics, Engineering)

Nice To Haves

Master’s degree or MBA preferred

Responsibilities

Identify and quantify opportunities across existing and potential partners, including whitespace analysis and share-of-wallet opportunity sizing.
Develop and own frameworks for tracking and improving key sales performance metrics across partner lifecycle stages—from onboarding through growth and retention.
Serve as a strategic partner to RevOps, Sales Leadership, Partner Strategy, and B2B Marketing, providing the analytical foundation for revenue-driving initiatives.
Conduct partner-level forecasting to project performance based on historical trends, cohort modeling, and macroeconomic indicators.
Lead market research and prospect intelligence efforts for potential enterprise partnerships, including: Web scraping and secondary data gathering to assess market footprint, business scale, and potential vertical integration. Estimating current and potential volume and revenue impact for use in executive-level partnership pitches.
Collaborate with sales team members to produce high-impact, data-driven materials in response to RFPs, including tailored opportunity sizing and performance projections.
Design lead scoring and qualification models to improve top-of-funnel lead quality and reduce disqualification rates.
Partner with SMB Sales and Customer Success teams to identify behavioral and operational signals for successful onboarding and partner retention.
Support territory planning, rep-level performance optimization, and resource allocation across inside sales, field teams, and customer success groups.
Analyze marketing and sales funnel effectiveness to drive improvements in campaign targeting, messaging, and ROI.
Analyze B2B marketing campaign effectiveness across acquisition, onboarding, and retention, with a focus on optimizing lifetime value.
Build predictive models for churn risk, engagement trends, and bottlenecks in the sales funnel.
Evaluate the impact of onboarding, training, and enablement initiatives on partner performance and revenue contribution.
Collaborate with Data Science teams to build and deploy machine learning models for lead prioritization, partner segmentation, location-based targeting, and behavior forecasting.
Apply advanced techniques such as probabilistic matching, multi-touch attribution, and geographic optimization to enhance partner insights.
Design and evaluate experiments aimed at improving sales performance, partner onboarding, product adoption, and campaign strategy.
Synthesize experimental results into actionable insights that improve conversion rates and increase sales team effectiveness.