Capital One
Senior Associate, Data Scientist - Applied AI
$136K–$169K
New York, NY +1 · Senior · Full-time · Posted Sep 25, 2026
- Location
- New York, NY
McLean, VA - Experience
- Bachelor’s route requires 2 years of data analytics experience. Preferred: at least 2 years in Python, Scala, or R; machine learning; and SQL; at least 1 year in AI, Information Retrieval, Deep Learning, or NLP.
- Education
- Bachelor’s degree in a quantitative field plus required experience, or a Master’s degree in a quantitative field or an MBA with a quantitative concentration. Degree must be held or expected by the scheduled start date.
- Visa sponsorship
- Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
About the job
Build and deploy enterprise Generative AI solutions, including multi-agent systems and advanced RAG pipelines, for Commercial Bank business processes.
What you'll do
- Partner with data scientists, machine learning engineers, and product managers to deliver Generative AI solutions.
- Build multi-agent systems and advanced RAG pipelines using numeric and textual data.
- Develop Generative AI models and pipelines through context engineering, fine-tuning, evaluation, validation, and deployment.
What they ask for
- Bachelor’s degree in a quantitative field plus 2 years of data analytics experience, or a Master’s degree in a quantitative field or an MBA with a quantitative concentration.
- Hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
- Experience building, validating, and backtesting statistical models; familiarity with clustering, classification, sentiment analysis, time series, and deep learning.
Nice to have
- Master’s or PhD in a STEM field.
- Experience with Python, Scala, or R; machine learning; SQL; or AI, Information Retrieval, Deep Learning, or NLP.
Pay
USD $135,600 - $154,800 base salary (McLean, VA); USD $148,000 - $168,900 base salary (New York, NY)
Tools
Python, PyTorch, LangChain, AWS, Spark, Vector Databases, Scala, R
AI focus
Build enterprise Generative AI, multi-agent systems, and advanced RAG pipelines; develop models and pipelines through context engineering, fine-tuning, evaluation, validation, and deployment.
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