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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Associate, Data Scientist - Applied AI - **Company:** Capital One Financial Corporation - **Location:** New York, NY, United States - **Experience:** Expert - **Salary:** $135,600.0 - $154,800.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Information Retrieval, Python (Programming Language), Machine Learning, Open Source Technology, Standard Sql, Sentiment Analysis, Cloud Platform System, Pytorch, Large Language Models, Multi-Agent Systems, Apache Spark, Deep Learning, Generative AI, Information Technology, Data Analytics - **Published:** September 26, 2026 - **Apply:** https://www.capitalonecareers.com/job/new-york/senior-associate-data-scientist-applied-ai/1732/101136128288 ## About the Role * Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. * Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. * Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms. * Statistically-minded. You've built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning., * Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: + A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics + A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration, * Master's Degree in "STEM" field (Science, Technology, Engineering, or Mathematics), or PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) * At least 2 years of experience in Python, Scala, or R * At least 2 years of experience with machine learning * At least 2 years of experience with SQL * At least 1 year of experience in AI, Information Retrieval, Deep Learning, or NLP ## Description The Commercial Bank Applied AI team is at the forefront of embedding Generative AI directly into core business processes. We specialize in building enterprise-grade architectures using advanced techniques such as Multi-Agent Systems, Advanced RAG, Context Engineering, Tool-Calling Frameworks etc. The ideal candidate is deeply passionate about the practical applications of Generative AI and brings hands-on experience in machine learning and AI, gained through either professional industry work or rigorous academic research. In this role, you will: * Partner with a cross-functional team of data scientists, machine learning engineers, and product managers to deliver Generative AI solutions customers love. * Leverage a broad stack of technologies-Python, PyTorch, LangChain, AWS, Spark, and Vector Databases-to build Multi-Agent systems and advanced RAG pipelines over vast volumes of numeric and textual data. * Build Generative AI models and pipelines through all phases of development, from context engineering through fine-tuning, evaluation, validation, and deployment. * Flex your interpersonal skills to translate the complexity of your work into tangible business goals. ## Related Videos - [Pioneering AI Assistants in Banking](https://www.wearedevelopers.com/videos/1627-pioneering-ai-assistants-in-banking) - [How building an industry DBMS differs from building a research one](https://www.wearedevelopers.com/videos/768-how-building-an-industry-dbms-differs-from-building-a-research-one) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Let's Get Aggregated: Custom UDAFs in Spark ](https://www.wearedevelopers.com/videos/1649-let-s-get-aggregated-custom-udafs-in-spark) - [Analytics in the Age of Agentic AI: A tour of ClickHouse and Langfuse](https://www.wearedevelopers.com/videos/100240-analytics-in-the-age-of-agentic-ai-a-tour-of-clickhouse-and-langfuse) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [How to start an AI project for a good cause and boost your career](https://www.wearedevelopers.com/magazine/15-how-to-start-an-ai-project-for-a-good-cause-and-boost-your-career) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)