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Senior Credit AI Scientist (Fintech)
173 500 - 234 500$
Описание вакансии
Текст:
TL;DR
Senior Credit AI Scientist (Fintech): Develops cutting-edge credit risk AI/ML models for new lending products, contributing to credit risk AI science initiatives with hands-on ownership of the model lifecycle. Focus on designing and building efficient and reusable data pipelines for feature generation and ensuring model fairness and compliance with relevant regulatory frameworks.
Location: Oakland, Charlotte, Culver City, San Diego, London, Bangalore, and New York City
Salary: $173,500.00 - 234,500
Company
is focused on championing financial progress for its more than 140 million members globally.
What you will do
- Design, build, deploy, evaluate, defend, and monitor machine learning models to predict credit risk for various short-term lending products.
- Collaborate with credit policy, product, and fraud risk teams to ensure models align with business goals and product offerings.
- Build efficient and reusable data pipelines for feature generation, model development, scoring, and reporting using Python, SQL, and Machine Learning and AI infrastructures.
- Contribute to the evolution of the data and machine learning infrastructure to improve the 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.
Requirements
- Advanced Degree (Ph.D. / MS) in Computer Science, Data Science, AI, Mathematics, Statistics, Physics or a related quantitative discipline.
- 3-7 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.
- Deep understanding of credit risk modeling concepts, including PD calibration, reject inference, adverse action logic, and risk segmentation.
Nice to have
- 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.
Culture & Benefits
- 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 to ensure efficient and effective use of data science in ways that make an immediate, substantial, and sustainable impact.
- is proud to be an Equal Employment Opportunity Employer.
- Committed to a diverse and inclusive work environment.
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