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San Diego, California, United States
Onsite
Mulligan Funding is a San Diego based provider of funding to the Small and Medium Sized Business market. We are building a deeply researched and first-of-it’s-kind, Agentic AI complete funnel automation strategy. Mulligan has decades of deep credit underwriting and analytics expertise, combined with rich data from almost a million applications and billions of dollars funded via a wide loan size of $10k to $10 million. We are a mission-driven company, focused on solving the SMB market’s access to the fast and affordable capital they need to thrive by re-inventing how credit risk is measured, priced, and negotiated. We combine a generational-technology with unwavering integrity and a human touch.
We are seeking an analytical, proactive, and curious Staff Sales Analyst to join our team in San Diego, CA. In this role, you will sit at the intersection of Sales, Operations, Data Engineering, and Data Science, acting as the primary engine for actionable sales insights and funnel metrics.
You will define and track the health of our sales funnel, partner closely with frontline operations to measure team performance, and collaborate with technical teams to scale data pipelines and predictive models. We are looking for an AI-native practitioner—someone eager to adopt and experiment with modern AI tools, automated workflows, and Generative AI technologies to accelerate insight delivery and transform traditional sales operations.
Funnel Analytics & Sales Insights:
Produce actionable insights to optimize conversion, velocity, and revenue across all acquisition and sales channels.
Design, build, and maintain core metrics and KPIs defining the health of the end-to-end sales funnel (e.g., Lead-to-Application, Approval-to-Acceptance, Funded Rates, and SLA timelines).
Perform regular diagnostic deep-dives to pinpoint friction points, application drop-offs, and operational bottlenecks.
Operations & Process Measurement:
Work directly with Sales and Operations leadership to understand frontline workflows, customer journeys, and deal dynamics.
Partner closely with Sales and Operations leaders to navigate diverse stakeholder perspectives, build consensus, and deliver actionable deal prioritization and pipeline optimization recommendations.
Manage day-to-day and deal-by-deal operational friction, translating feedback and business requirements into structured analytical frameworks and executive dashboards.
Establish measurement frameworks to evaluate team performance, incentive structures, channel efficiency, and capacity planning.
Data Engineering & Data Science Partnership:
Serve as the strategic conduit and bridge between business stakeholders, Sales leadership, and technical build teams to align business priorities with technical execution.
Collaborate closely with Data Engineers and Data Scientists to productionalize metrics and ensure a robust, single-source-of-truth data infrastructure.
Help scope, validate, and test scalable machine learning models and analytical frameworks aimed at improving funding conversion rates and targeting strategies.
AI-Native Transformation & Strategic Innovation:
Lead the adoption, testing, and scaling of cutting-edge AI technologies (e.g., LLM-based analytics assistants, automated insight generation, prompt engineering tools, and conversational analytics platforms) to transform traditional sales operations.
Automate routine reporting and data extraction workflows using modern tools to drastically reduce manual effort across business units.
Drive strategic efficiency initiatives by continuously evaluating emerging technologies and embedding advanced analytical capabilities into day-to-day operations.
Education: Undergraduate degree (B.A. / B.S.) in Business Analytics, Finance, Economics, Statistics, Information Systems, or a related quantitative field.
Experience: 5–7+ years of experience supporting Sales, Marketing, or Revenue Operations in an analytical capacity (Fintech, Financial Services, or high-growth B2B environment preferred), with a proven track record of driving strategic operational change.
Technical Skills:
Advanced Excel Skills: Highly proficient with complex formulas, pivot tables, scenario modeling, and dynamic reporting constructs.
Python Skills: Exposure to Python for data manipulation (Pandas, NumPy) and workflow automation.
SQL / BI Tools: Experience querying relational databases or building dashboards (Tableau, Power BI, Looker).
Communication & Leadership: Exceptional written and verbal communication skills. Demonstrates assertiveness and constructive challenge to push back effectively on assumptions, advocate for data-driven decisions, and articulate complex insights to executive stakeholders.
Mindset: Curiosity-driven with an "AI-first" attitude toward problem-solving, process efficiency, and continuous learning.
