Position Details
About this role
This role involves developing machine learning models and data insights to modernize anti-money laundering efforts at Capital One. The data scientist will work across cloud platforms, build predictive models, and deploy AI tools to improve risk detection.
Key Responsibilities
- Partner with cross-functional teams
- Build production-ready data pipelines
- Develop and deploy machine learning models
- Fine-tune large language models
- Translate complex data work into business goals
Technical Overview
The technical environment includes Python, AWS, Snowflake, Spark, and open-source data science tools. The focus is on building scalable data pipelines, deploying machine learning models, and leveraging large language models for risk management.
Ideal Candidate
The ideal candidate is a mid-level data scientist with 3+ years of experience in machine learning, statistical modeling, and cloud platforms like AWS. They should be proficient in building data pipelines, deploying models, and working with large datasets to develop risk management solutions.
Must-Have Skills
Nice-to-Have Skills
Tools & Platforms
Required Skills
Hard Skills
Soft Skills
Industry & Role
Keywords for Your Resume
Deal Breakers
Lack of experience with AWS or cloud platforms, No experience with machine learning or data pipelines, Insufficient statistical modeling skills, No familiarity with large language models, Less than 3 years of relevant experience
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