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Credit Karma

Senior Credit AI Scientist - Consumer Risk

Reposted 4 Days Ago
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Hybrid
Mountain View, CA
174K-235K Annually
Mid level
Easy Apply
Hybrid
Mountain View, CA
174K-235K Annually
Mid level
The Senior Credit AI Scientist will develop AI/ML models to assess credit risk for new lending products, collaborating with various teams, ensuring model fairness and compliance, and improving data science infrastructure.
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Intuit Credit Karma is a mission-driven company, focused on championing financial progress for our more than 140 million members globally. While we're best known for pioneering free credit scores, our members turn to us for everything related to their financial goals, including identity monitoring, applying for credit cards, shopping for insurance and loans (car, home and personal) and savings accounts and checking accounts* – all for free. Credit Karma has grown significantly through the years: we now have more than 1,700 employees across our offices in Oakland, Charlotte, Culver City, San Diego, London, Bangalore, and New York City.

*Banking services provided by MVB Bank, Inc., Member FDIC

Intuit’s Consumer Group, including TurboTax and Credit Karma, empowers millions of individuals to take control of their finances. TurboTax simplifies tax preparation and enables our customers to file with confidence. By harnessing the power of data and artificial intelligence (AI), we continuously innovate and evolve our consumer offerings to deliver even greater value.

As we expand into Consumer Lending within the Consumer Group, Intuit Credit Karma is looking for an innovative, experienced, and hands-on Senior AI Scientist to join our Consumer Risk AI Science team. In this role, you’ll develop cutting-edge credit risk AI/ML models for new lending products. Join a collaborative and inventive team of AI scientists and machine learning engineers where your work will have a direct impact on hundreds of thousands of customers.

 What you’ll do:
  • Contribute to the credit risk AI science initiatives for the new and evolving Money product offerings focusing on the lending domain, including complete hands-on ownership of the model lifecycle, sharing ownership of success and key results at the program-level, and driving the data  strategy across all involved teams.
    • Design, build, deploy, evaluate, defend, and monitor machine learning models to predict credit risk for various short-term lending products (e.g., tax refund advances, BNPL, installment loans, single payment loans, and early wage access)
    • Collaborate with credit policy, product and fraud risk teams to ensure models align with business goals and product offering to drive actionable lending decisions
    • Build efficient and reusable data pipelines for feature generation, model development,  scoring, and reporting using Python, SQL, and both commercially available and proprietary Machine Learning and AI infrastructures 
    • Deploy models in a production environment in collaboration with other AI scientists and machine learning enginers 
    • Ensure model fairness, interpretability, and compliance with FCRA, ECOA, and other relevant regulatory frameworks 
  • Contribute to the evolution of our data and machine learning infrastructure within the Intuit ecosystem to improve efficiency and effectiveness of AI science solutions.
  • Research and implement practical and creative machine learning and statistical approaches suitable for our fast-paced, growing environment.
 What’s great about the role:
  • Solve hard, meaningful problems giving customers access to their hard-earned money alongside fun, smart people.
  • Experience professional growth and encourage growth throughout the team.
  • Work cross functionally (with executives, engineering, policy & rules, product, analytics, operations and other AI science teams) to ensure efficient and effective use of data science in ways that make an immediate, substantial, and sustainable impact
 Minimum Basic Requirements:
  • Advanced Degree (Ph.D. / MS) in Computer Science, Data Science, AI, Mathematics, Statistics, Physics or a related quantitative discipline
  • 3-6 years of work experience in AI Science / Machine Learning and related areas
  • Authoritative knowledge of Python and SQL
  • Relevant work experience in fintech credit risk, with deep understanding of payment systems, money movement products, banking, and  lending
  • Experience leveraging credit bureau, tax and cash flow data in credit risk model development
  • Experience with and deep understanding of developing, deploying, monitoring and maintaining a variety of machine learning techniques, including but not limited to, deep learning, tree-based models, reinforcement learning, clustering, time series, causal analysis, and natural language processing.  
  • Deep understanding of credit risk modeling concepts, including PD calibration, reject inference, adverse action logic, and risk segmentation
  • Ability to quickly develop a deep statistical understanding of large, complex datasets
  • Expertise in designing and building efficient and reusable data pipelines and framework for machine learning models
  • Strong business problem solving, communication and collaboration skills
  • Ambitious, results oriented, hardworking, team player, innovator and creative thinker

Preferred Qualifications:
  • Proficiency in deep learning ML frameworks such as TensorFlow, PyTorch, etc.  
  • Work experience with public cloud platforms (especially GCP or AWS) and workflow orchestration tools like Apache Airflow 
  • Strong background in MLOps infrastructure and tooling, particularly Vertex AI or AWS SageMaker, including pipelines, automated retraining, monitoring, and version control
  • Experience with experimentation design and analysis, including A/B testing and statistical analysis

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. The expected base pay range for this position in Bay Area California is $173,500.00 - 234,500. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.

Equal Employment Opportunity:

Credit Karma is proud to be an Equal Employment Opportunity Employer. We welcome all candidates without regard to race, color, religion, age, marital status, sex (including pregnancy, childbirth, or related medical condition), sexual orientation, gender identity or gender expression, national origin, veteran or military status, disability (physical or mental), genetic information or other protected characteristic. We prohibit discrimination of any kind and operate in compliance with applicable fair chance laws. 

Credit Karma is also  committed to a diverse and inclusive work environment because it is the right thing to do. We believe that such an environment advances long-term professional growth, creates a robust business, and supports our mission of championing financial progress for everyone. We offer generous benefits and perks with a single eye to nourishing an inclusive environment that recognizes the contributions of all and fosters diversity by supporting our internal Employee Resource Groups. We’ve worked hard to build an intensely collaborative and creative environment, a diverse and inclusive employee culture, and the opportunity for professional growth. As part of the Credit Karma team, your voice will be heard, your contributions will matter, and your unique background and experiences will be celebrated.

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Credit Karma is strongly committed to protecting personal data. Please take a look below to review our privacy policies:

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Top Skills

Apache Airflow
AWS
GCP
Python
PyTorch
SQL
TensorFlow
HQ

Credit Karma Oakland, California, USA Office

Credit Karma Oakland is located in the heart of downtown, with a ton of great restaurants, shops and above a subway and bus stop.

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