Business Intelligence Lead

Point Predictive; San Diego (CA); On-site; USD 100,000 - 150,000; Full time

Benefits offered by this job

In-person team culture

San Diego HQ

Job summary

Point Predictive, an AI company based in San Diego, seeks a Business Intelligence Analyst to turn lending data into proof using retrospective studies. You will design end-to-end analyses, run large loan-originations datasets, and translate results into clear ROI narratives for prospects and customers.

You will also support discovery calls, demos, and sales materials, while building reusable analytics assets for faster, defensible decisions.

Qualifications

• 5+ years in a data-focused analytical role such as BI Lead or BI Analyst
• Strong ability to translate data findings into a story for customers
• Excellent communication with non-technical executives and customers
• Proficiency with SQL and hands-on experience with large datasets
• Experience with analysis and visualization tools (Excel and BI tools like Sigma)
• Familiarity with AI models or LLMs to accelerate analytics is a plus

Responsibilities

• Lead end-to-end retrospective data studies to prove product value
• Work with large loan origination datasets ensuring data quality and defensible methodology
• Frame business problems and design analyses to meet customer needs
• Translate findings into ROI-focused business cases and narratives
• Present results to customer stakeholders across risk, lending, and finance
• Develop reusable queries, templates, and documentation for repeatable studies
• Own data-quality validation of inputs and results for customer-facing outputs
• Collaborate with sales to create discovery materials and product feedback to guide development

Skills

SQL

Data storytelling

Customer-facing

Data analysis

Communication

Tools

Sigma

BigQuery

Snowflake

Excel

Job description

Point Predictive is hiring a Business Intelligence Analyst to turn our unmatched lending data into proof. Demand for our products is quickly accelerating, and the fastest, most convincing way we demonstrate and prove value to prospects and customers is through retrospective data studies — analyses that take a lender's own historical loan data, run it against our risk intelligence, and quantify exactly what we would have caught, prevented, and improved.

This is a data-first role. About 80% of your time is spent designing and running these retro studies end to end: understanding what a customer is trying to solve, working through large loan-origination datasets, and translating the results into a clear, defensible business case. The remaining 20% supports our sales team directly — joining discovery calls, contributing to demos, and building the material they use to win and expand accounts.

Why Point Predictive

• 650+ enterprise customers — top-tier market leaders in auto, bank, credit union, and fintech
• $5 trillion in proprietary loan origination data — unmatched risk intelligence in the lending industry
• Proven outcomes: lenders cut fraud losses 40–60% and auto-approve up to 80% of qualified applications
• Fast-growing AI company — clear market position, strong product-market fit, expanding customer base
• High-impact analytics role — your studies are the proof behind every major deal, from first evaluation through expansion
• In-person team culture — collaborative San Diego HQ with speed, low bureaucracy, and direct leadership access

What You Will Do

You own the analytical work that proves our value. Every study starts from a customer's business problem and ends with a result they can act on.

• Retro study execution: run retrospective studies end to end — secure and ingest customer historical loan data, run it against our scores and models, and quantify fraud caught, losses avoided, approval lift, and the other outcomes that matter to the lender
• Large-dataset analysis: work confidently with large, imperfect loan-origination datasets — clean, join, validate, and analyze millions of records with a constant eye on data quality and defensible methodology
• Business framing: begin every study by understanding the customer's workflows, goals, and success criteria, then design the analysis to answer the questions they actually care about. Work alongside Sellers to create the story from the data intelligence.
• Insight translation: turn analytical findings into clear ROI business cases and narratives that land equally well with a data analyst and with a CFO who needs a defensible number before signing
• Results presentation: present findings directly to customer stakeholders across risk, lending, and finance
• Methodology & repeatability: build reusable queries, templates, and documentation so studies get faster, and more consistent over time
• Data-quality ownership: validate inputs and results so every number we put in front of a customer holds up to scrutiny
• Using the power of data to tell the story and finding using your curiosity, strong data intuition, and experience to identify new ways to drive higher result performance.

The rest of the role puts your analytical perspective directly in front of prospects alongside the sales team.

• Discovery support: join discovery calls to understand each customer's data environment, integration setup, and success criteria, and to scope what a study would require
• Demo support: contribute to product demonstrations by grounding them in real data and relevant results, so what customers see reflects outcomes they can expect
• Sales material: create the assets the sales team uses to penetrate and expand accounts
• Product feedback: close the loop between what you see in the data and in discovery and what the product team builds next

What You Bring

Required

• 5+ years in a data-focused analytical role — Business Intelligence Lead, Business Intelligence Analyst, Quantitative Analyst, or similar
• Business orientation: you understand customer’s objective and goals and work instinctively to connect data findings to the customer's underlying business need.
• Have a strong ability to translate information into a story or talk-track and communicate clearly and successfully to the customer.
• Strong SQL and hands-on experience working with large datasets — cleaning, joining, validating, and analyzing at scale
• Proficiency with analysis and visualization tooling: SQL, advanced Excel, and BI tools such Sigma
• Strong technical communication: you can take a complex analysis and make it land with a non-technical executive

Strong understanding and/or experience using AI models such as Claude, Coco/Snowflake, Gemini in BigQuery, ChatGPT with Advanced Data Analysis, or similar LLM models to assist in running complex analytics, automate tasks, schedule automations, build performance dashboards, and building executive level presentations to make your data analysis tell a story that the customer’s executive team could understand

Strongly Preferred

• Fintech or financial services background: lending, auto finance, banking, fraud detection, or credit risk
• Familiarity with loan-origination data, credit underwriting workflows, or lending infrastructure
• Experience building ROI models or quantifying business value from data for external stakeholders
• Comfortable in a customer-facing setting and can confidently present findings to executive level leadership
• Statistical rigor: sampling, significance, and defensible methodology when working with large datasets
• Hands-on AI/LLM experience for accelerating analysis workflows and design (ChatGPT, Claude, or similar)

About Point Predictive

Point Predictive is an AI company on a mission to eliminate fraud in the lending ecosystem. Our technology helps banks, auto lenders, credit unions, and finance companies identify which borrowers are misrepresenting information on loan applications — enabling smarter, faster lending decisions.

We serve more than 650 customers and have built a proprietary risk intelligence platform from over $5 trillion in historic loan originations. Our clients are the most sophisticated lenders in the auto, bank, credit union, and fintech markets. Our solutions deliver proven results at enterprise scale: up to 80% auto-approval rates on qualified applications, with fraud detection that traditional methods miss entirely.

We are a focused, fast-moving team headquartered in downtown San Diego.