Senior Staff AI Scientist, Consumer Risk

Intuit

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Mountain View, CA
Salary
$226,000–$306,000 / yr
Posted
6 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $207k
This role $266k
$145k most similar roles pay here $323k

This role pays more than 85% of similar roles. Most pay $162,000–$251,521 — the shaded band above. At the midpoint, this role pays about $266k versus about $207k for comparable roles.

Based on 240 similar postings.

Employer

About Intuit

Intuit is a financial software company known for products like TurboTax, QuickBooks, Mint, and Credit Karma, helping consumers and small businesses manage their finances and taxes. Industry: Financial Software & Technology

Intuit currently has 174 open roles on FindRole.

Listed pay typically runs $202,500–$274,000 across 152 roles with salary data.

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At a glance

TL;DR · Senior Staff AI Scientist, Consumer Risk

As a Senior Staff AI Scientist - Consumer Risk, you will join the Consumer Risk AI Science team to serve as a player-coach focused on credit and fraud risk. You will build, deploy, and monitor machine learning models for consumer lending, fast-money products, and banking services across three business verticals. Your daily work involves managing the end-to-end model lifecycle, overseeing data strategies using sources like credit bureaus and cashflow transactions, and ensuring regulatory compliance with frameworks such as SR 11-7, FCRA, and ECOA. You will utilize Python, SQL, and deep learning frameworks like TensorFlow or PyTorch within AWS SageMaker and GCP Vertex AI environments. The role addresses complex problems in risk modeling, including fraud detection, account takeover prevention, and credit underwriting for products like tax refund advances and installment loans.

What you'll do

  • Build, deploy, and monitor credit risk and fraud risk AI/ML models across multiple business verticals.
  • Define the modeling strategy by setting technical direction, reviewing team work, and removing roadblocks.
  • Manage the data strategy by governing internal and third-party data sources to build proprietary risk attributes.
  • Own the end-to-end model lifecycle across both AWS SageMaker and GCP Vertex AI cloud infrastructures.
  • Ensure model governance and regulatory compliance regarding fair lending, fraud prevention, and reporting requirements.
  • Partner with cross-functional teams like Product, Engineering, and Legal to integrate models into product launches.
  • Lead hiring, onboarding, and the adoption of Agentic AI tools to automate the model development lifecycle.

What we're looking for

  • Advanced degree (Ph.D. or MS) in a quantitative field like Computer Science, Data Science, AI, Mathematics, Statistics, Econometrics, or Physics.
  • 8+ years of experience in AI Science and Machine Learning successfully delivering data-driven products.
  • Authoritative knowledge of Python and SQL.
  • Relevant fintech experience in credit risk and/or fraud risk modeling with a deep understanding of payment systems and banking.
  • Hands-on expertise developing, deploying, and monitoring various machine learning techniques including deep learning, tree-based models, and NLP.
  • Experience leveraging credit bureau, tax, cashflow, identity, and behavioral data for risk model development.
  • Deep understanding of credit risk concepts and fraud typologies such as synthetic ID, ACH fraud, and account takeover.
  • Expertise in designing efficient data pipelines and managing MLOps infrastructure on cloud platforms like AWS or GCP.

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