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As a Senior Manager of Data Engineering at Capital One, you will lead a team to design, develop, and implement technical solutions, focusing on data engineering and cloud-based solutions, while also managing team collaboration and mentoring.
Responsible for managing daily, monthly delivery and issue remediation of financial data and reports in the Capital Markets Analytics - Automation and Data team. Collaborate with business partners to analyze regulations, perform data analysis using SQL and Python, drive process improvements, and communicate with senior management.
Senior Manager, Data Science role at a Fortune 200 company specializing in credit card industry disruption and data-driven decision-making. Responsibilities include partnering with cross-functional teams, building machine learning models, leveraging technologies like Python and AWS, and translating complex work into business goals. Ideal candidate is customer-focused, a leader, technically proficient, and a data guru. Basic qualifications include a Bachelor's Degree with 7 years of experience in data analytics or a Master's Degree with 5 years of experience.
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As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records. The role involves harnessing transformer model architectures, managing large-scale data annotation projects, collaborating with machine learning engineers, and leveraging a broad stack of technologies to automate workflows using huge volumes of text audio, and vision data.
The Principal Associate , Data Science - Servicing Intelligence at Capital One is responsible for harnessing the power of transformer model architectures, fine-tuning large language models, managing data annotation projects, building machine learning solutions, collaborating with stakeholders, and leveraging a broad stack of technologies to automate workflows using text, audio, and vision data.
The Manager, Capital Markets and Risk - Automation and Data team at Capital One is responsible for analyzing regulations, managing data, and performing calculations to create analytics with business value. They collaborate with business partners to identify and problem solve issues, deliver insights, and drive decision-making. Responsibilities include analyzing regulations' impact, managing data delivery, performing user acceptance testing, and driving process improvements. Basic qualifications include a Bachelor's Degree and at least 4 years of financial modeling experience. Preferred qualifications include 6+ years of financial industry experience, CPA or Master's Degree, and proficiency in SQL and Python.
Senior Manager, Data Science role at a Fortune 200 company specializing in data-driven decision-making. Responsibilities include leading a team to deliver customer-centric products using machine learning technologies and collaborating with cross-functional teams. Ideal candidate is customer-focused, a leader, technically skilled, and proficient in big data analysis.
As a Senior Manager, Data Science at Capital One, you will partner with a cross-functional team to deliver products customers love, build machine learning models, and leverage a broad stack of technologies. The ideal candidate is customer-focused, a leader, technically proficient, and a data guru.
As a Principal Data Scientist at Capital One, you will lead the development of machine learning models to improve customer experiences and business outcomes. You will research and apply emerging technologies in AI, engage with business and product teams, and ensure robust operational integration of models to serve millions of customers.
As a Principal Data Scientist, you will leverage advanced machine learning techniques to build production-ready models and conduct research in AI, focusing on embedding and transformer models. You'll collaborate with product and engineering teams to analyze customer behavior and enhance business outcomes across various domains.
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