---
title: 'Senior ML Data Scientist (Credit Risk) at Zed'
canonical: 'https://feeny.ai/job/senior-ml-data-scientist-credit-risk-zed-san-francisco-5ajvgnd0y8s6'
type: 'job'
last_seen: '2026-09-07'
---

# Senior ML Data Scientist (Credit Risk) at Zed

- **Company:** Zed
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-06-16
- **Last confirmed live:** 2026-09-07
- **Apply:** https://jobs.ashbyhq.com/zedfinancial/da9d816a-2b62-4f2b-be8c-33b21ad9ec65

## Job description

## About Zed

Zed is building the first AI-native, licensed neobank in the Philippines designed to democratize access to premium financial services for young professionals in global markets. The current banking system is broken, often shutting out the world’s youngest and fastest-growing consumer classes—we’re here to fix it.

Our team is uniquely positioned to solve this. We are Stanford engineers and former YC founders who have spent our careers at the intersection of banking and hyper-growth startups like Square, Facebook, and Box. We’ve been here before, having previously built and exited Symple (YC W'17), a fast-growing B2B payments company.

We are backed by world-class investors, including Accel, Valar, Immad Akhund (Mercury), Dalton Caldwell (Y Combinator), and Kunal Shah (Cred).

## THE ROLE

Zed underwrites credit using foundation models that profile risk from transaction data, financial documents, and other structured and unstructured sources — not credit scores. That means our ML stack looks less like a traditional bank's and more like a modern AI system: embedding models, transformer architectures, and LLM-assisted data pipelines sitting alongside classical credit and fraud models. We're hiring a Senior ML Data Scientist to work directly with our data lead across all of it — core credit models, account management, and fraud detection — with a particular focus on pushing the frontier of how we represent and reason about financial data. This is a senior role, which means we expect you to have opinions about the stack, shape how we build, and set the technical bar for ML at Zed as the team grows. If you're the kind of person who's deploying neural networks and transformer-based models in production rather than just reading about them, this role was written for you.

## WHAT YOU’LL DO

- Work closely with our data lead on the full risk model suite: core credit decisioning, account management, and fraud detection
- Own data preparation pipelines for model inputs — including using NNs and LLMs to represent transaction data as vector embeddings for quantitative analysis
- Experiment with and deploy neural network and transformer-based architectures in the underwriting process
- Build agent scaffolding and harnesses within underwriting workflows — this is active, in-production experimentation, not research
- Design and deploy fraud detection models combining rule-based systems and ML to identify suspicious activity in real time
- Engineer features from structured and unstructured data sources
- Develop monitoring systems to keep models accurate and reliable in production
- Partner with engineering and risk operations to integrate model outputs into decisioning systems
- Influence technical direction — you'll have a seat at the table when we make decisions about how ML is built and deployed at Zed

## WHAT YOU BRING

- 7+ years of experience in applied ML or data science with a focus on credit risk, fraud, or financial services
- Hands-on experience with LLMs, embeddings models, or transformer-based architectures — not just familiarity, but production or near-production deployment
- Proficiency in Python and SQL; experience with frameworks such as XGBoost, LightGBM, PyTorch, or similar
- Strong feature engineering skills — you know how to extract signal from messy, sparse, or heterogeneous financial data
- Solid statistical foundation: anomaly detection, supervised classification, model calibration, experimentation design
- Experience building and monitoring production models including alerting on performance degradation and concept drift
- Familiarity with both rule-based and model-driven approaches — and when to use each
- A point of view on how ML systems should be built — you can articulate tradeoffs, push back on bad decisions, and bring junior team members along
- Comfort operating as a senior ML voice at an early-stage company — you own problems end-to-end and set the standard for others
- Experience with emerging markets or data-sparse environments is a plus

We hire exceptional people from diverse backgrounds because different perspectives build better products.

If you’re excited about this role but don’t check every box, apply anyway. We value potential, ownership, and alignment with our values more than perfect résumés.

We are an equal opportunity employer and do not discriminate based on legally protected characteristics. We provide reasonable accommodations throughout the hiring process.

Compensation includes salary, equity, and benefits. Final offers are based on role scope, location, and experience.

## About Zed

## Company Overview
- **One-liner**: Zed builds a modern, AI-powered credit card and financial platform designed for young professionals in Southeast Asia, offering no-interest credit, unlimited virtual cards, and transparent fees.
- **Entity Type**: Private (Series A; total funding $22.5M)
- **Headquarters**: San Francisco, California, United States (with operations in Manila, Philippines)
- **Founded**: Year not publicly stated; launched in Philippines in 2024
- **Founders**: Steve Abraham (Co-founder) & Danielle Cojuangco Abraham (Co-founder & Co-CEO)

## Core Business
- **Primary industry**: Financial Services (Consumer Fintech)
- **Target customers**: B2C; specifically young, college-educated professionals in Southeast Asia (Generation Z and Millennials) who are underserved by traditional credit systems.
- **Mission statement**: "To build a bank for the next generation that feels like a great private banker," unlocking wealth creation for young people by democratizing access to responsible credit.

## Products & Services
- **[Zed Credit Card]**: A premium Titanium Mastercard with no interest, no foreign transaction fees, and unlimited virtual cards. Features include a data-driven application process that uses AI to underwrite creditworthiness from non-traditional data (transaction data, financial documents), flexible installment plans, instant card locking, and single-use virtual cards for online security. Type: Fintech product (credit card + mobile app).

## Market Standing
- **Valuation**: Not disclosed
- **Key Metric**: Total funding of **$22.5M** (Seed: $6M led by Valar Ventures; Series A: $16.5M led by Accel). Waitlist has nearly **200,000 sign-ups**; customer base has **grown by 10x** and monthly Gross Merchandise Value (spend) has grown by **~500%** since the beginning of 2025.
- **Notable Investors/Partners**: Accel, Valar Ventures, Immad Akhund (CEO of Mercury), Dalton Caldwell (former Y Combinator). Issued in partnership with Mastercard. Regulated by the Philippine Central Bank (BSP).
- **Growth Signals**: Rapid growth in user base and transaction volume; Series A round led by top-tier VC Accel; strong word-of-mouth waitlist; expansion of an AI-driven underwriting model targeting a massive underserved market (200M+ college-educated young professionals in emerging Asia). The team has grown **+35% YoY** (13 employees).

## Competitive Advantages
- **AI-native underwriting**: Uses foundational models to assess creditworthiness from alternative data (transaction history, financial documents) rather than relying on thin or nonexistent traditional credit bureau files. This unlocks credit for a huge "unscoreable" demographic.
- **Bespoke product for a generation**: The card is designed specifically for the spending habits of young Southeast Asians (travel, online shopping, peer-to-peer payments) with features like no foreign transaction fees and unlimited virtual cards.
- **Founder-market fit & licensing**: Founded by Stanford-educated engineers with deep fintech expertise (Symple, Y Combinator, Box) and local market knowledge. The company holds a financial institution license from the BSP, a significant regulatory moat.
- **Purpose-built tech stack**: Building a modern bank from scratch, free from legacy infrastructure, allowing for AI-driven, safety-critical consumer systems and multi-currency payments.

## Strategic Focus
- **Expand AI-driven credit products**: The current underwriting model is just the first application; the company plans to leverage proprietary AI models to build a wider suite of banking services for its target demographic.
- **Scale in Southeast Asia**: Currently focused on the Philippines as a beachhead market, with a long-term goal of serving young consumers across the region and globally.
- **Hire for product & engineering**: Actively recruiting product-minded engineers, designers, data scientists, and operations staff to build the core platform.
- **Key priorities**: Real-time credit decisioning with sparse data, building safety-critical consumer systems, multi-currency payments, and AI-driven customer experiences.

## Why Work Here
- **High-impact mission**: Opportunity to build a fundamental piece of financial infrastructure for a generation of 200M+ underserved young professionals in Asia.
- **Talent & culture**: The team is described as "ambitious" and "radically honest," composed of Stanford engineers and veterans from Square, Google, Stripe, Facebook, and Box. The environment is "people-first" and focused on technical excellence.
- **Work model**: Hybrid/Office for different teams. Product, Design, and Engineering teams are headquartered in **San Francisco**, while Operations and Risk are based in **Manila**.
- **Backing and stability**: Backed by top-tier investors (Accel, Valar) and key fintech leaders, providing strong financial runway and strategic guidance.
- **Cutting-edge work**: Engineers work on hard problems like AI underwriting, real-time credit, and multi-currency payments with the latest tools (foundational models, agent infrastructure).

## Sources
1. [zed.co](https://www.zed.co/)
2. [LinkedIn - Zed](https://www.linkedin.com/company/zedfinancial)
3. [Zed - Series A Announcement](https://www.zed.co/announcement-series-a/)
4. [Zed - Company Page](https://www.zed.co/company/)
5. [Zed - Careers Page](https://jobs.ashbyhq.com/zedfinancial)
6. [Zed - Card Page](https://www.zed.co/)

## Other roles at Zed

- [Lead Product Designer](https://feeny.ai/job/lead-product-designer-zed-san-francisco-bc3vavgakga1) — San Francisco, CA
- [Partnerships Lead](https://feeny.ai/job/partnerships-lead-zed-manila-zwf9wkssaxth) — Manila, Philippines
- [AI Engineer, Agent Infrastructure](https://feeny.ai/job/ai-engineer-agent-infrastructure-zed-san-francisco-7vmbp3jws5x3) — San Francisco, CA
- [Customer Experience & Operations Analyst](https://feeny.ai/job/customer-experience-operations-analyst-zed-manila-rdykm2kys848) — Manila, Philippines
- [Product Engineer](https://feeny.ai/job/product-engineer-zed-san-francisco-68gj119nab78) — San Francisco, CA
- [Data Scientist](https://feeny.ai/job/data-scientist-zed-manila-y8xamvdpgzgn) — Manila, Philippines