Drimva

Intuit

Staff AI Scientist -- Credit Karma

$210K–$284K

Oakland, California +1 · Staff · Full-time · Posted Aug 20, 2026

Location
Oakland, California
Mountain View, California
Experience
7+ years of industrial experience in Data Science, Machine Learning, or related areas; ideally in hyper-growth consumer Internet scenarios.
Education
MS in Computer Science, Mathematics, Statistics, Physics, or a related quantitative discipline.

About the job

Leads machine learning and AI initiatives that improve financial product recommendations, personalization, monetization, and member engagement at Credit Karma.

What you'll do

  • Identify high-impact uses of data and develop machine learning models, features, and personalization strategies for financial products.
  • Research and apply GenAI, deep learning, and recommender systems; design metrics and statistically grounded experiments.
  • Represent Data Science in cross-functional reviews, communicate technical work to business partners, and represent Credit Karma at external events.

What they ask for

  • MS in Computer Science, Mathematics, Statistics, Physics, or a related quantitative discipline.
  • 7+ years of industrial experience in Data Science, Machine Learning, or related areas.
  • Deep statistical understanding and ability to architect and develop next-generation ML systems.
  • Strong programming background, such as Python, Java, or SQL.

Nice to have

  • Experience driving monetization, member engagement, or long-term member value through AI.
  • Experience with large-scale AI systems, generative AI, AI infrastructure, data foundations, self-serve analytics, or ads products.

Pay

$230,000- $250,000 USD base salary; Oakland $209,500 - $283,500 USD base salary; Mountain View, CA $209,500- $283,500 USD base salary

Tools

Python, Java, SQL, GenAI, Deep Learning, Recommender systems

AI focus

Applies machine learning and GenAI to financial product recommendations, personalization, monetization, engagement, and large-scale AI systems.

Model-written summary · the original posting is authoritative

First seen Oct 28, 2026 · Last verified Nov 6, 2026 (UTC)