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8 Days Ago
Richmond, VA, USA
Hybrid
55,000 Employees
1-3 Years of Experience
55,000 Employees
1-3 Years of Experience
Fintech • Machine Learning • Payments • Software • Financial Services
As a Senior Associate, Data Science in People Analytics at Capital One, you will be responsible for designing and delivering modeling, research, and analysis to support talent strategies. The role involves applying data science skills to understand associate behavior, improve talent attraction and retention, and enhance executive pipeline diversity. The ideal candidate is passionate about human capital, innovative, creative, technical, and statistically-minded. Basic qualifications include a Bachelor's Degree with 2 years of data analytics experience, experience in open-source programming languages, machine learning, and relational databases. Preferred qualifications include a Master's Degree in a STEM field with 3 years of data analytics experience, proficiency in AWS, Python, PyTorch, Scala, R, machine learning, and SQL.
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+52 More
8 Days Ago
Mexico City, Cuauhtémoc, Mexico City, MEX
Hybrid
55,000 Employees
5-7 Years of Experience
55,000 Employees
5-7 Years of Experience
Fintech • Machine Learning • Payments • Software • Financial Services
As a Senior Software Engineer at Capital One, you'll collaborate with Agile teams to design, develop, and support technical solutions in full-stack development. You'll utilize various programming languages and cloud services to create robust solutions that enhance customer experiences.
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401-K
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+52 More
8 Days Ago
Richmond, VA, USA
Hybrid
55,000 Employees
201K-230K Annually
5-7 Years of Experience
55,000 Employees
201K-230K Annually
5-7 Years of Experience
Fintech • Machine Learning • Payments • Software • Financial Services
Lead a portfolio of diverse technology projects and a team of developers with deep experience in distributed microservices and full stack systems. Collaborate with digital product managers to deliver cloud-based solutions.
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401-K
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+52 More
8 Days Ago
Chicago, IL, USA
Hybrid
55,000 Employees
134K-162K Annually
5-7 Years of Experience
55,000 Employees
134K-162K Annually
5-7 Years of Experience
Fintech • Machine Learning • Payments • Software • Financial Services
The Senior Platform Engineer will develop and maintain solutions in Workday across various HR functions. Responsibilities include configuring business processes, delivering high-quality solutions, providing production support, collaborating with HR partners, and staying updated with Workday capabilities. The role requires effective communication with stakeholders and expertise in process improvements.
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401-K
401-K Matching
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+52 More
8 Days Ago
San Francisco, CA, USA
Hybrid
55,000 Employees
134K-162K Annually
5-7 Years of Experience
55,000 Employees
134K-162K Annually
5-7 Years of Experience
Fintech • Machine Learning • Payments • Software • Financial Services
As a Senior Platform Engineer at Capital One, you will develop and support Workday's Human Resource technology, focusing on configuration tasks across various areas including HCM and Recruiting. Your role will involve collaborating with product owners and stakeholders, identifying process improvement opportunities, maintaining documentation, and providing production support for Workday systems.
Top Benefits:
401-K
401-K Matching
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+52 More
8 Days Ago
Chicago, IL, USA
Hybrid
55,000 Employees
7+ Years of Experience
55,000 Employees
7+ Years of Experience
Fintech • Machine Learning • Payments • Software • Financial Services
The Senior Manager, Solutions Architect at Capital One leads the design and implementation of multi-platform technology solutions for their Credit Card business. This role includes managing technical conflicts, communicating solutions to stakeholders, and fostering relationships across various teams. The candidate will oversee architecture points of contact and adapt to evolving technology needs.
Top Benefits:
401-K
401-K Matching
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+52 More
8 Days Ago
Richmond, VA, USA
Hybrid
55,000 Employees
7+ Years of Experience
55,000 Employees
7+ Years of Experience
Fintech • Machine Learning • Payments • Software • Financial Services
Distinguished Engineer at Capital One responsible for defining the future of banking in the cloud and leading technical experts to drive innovation and optimize business outcomes. Promotes a culture of engineering excellence and mentors internal talent. Specializes in Consumer Data team mission to understand and serve customers.
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401-K
401-K Matching
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8 Days Ago
Richmond, VA, USA
Hybrid
55,000 Employees
134K-162K Annually
5-7 Years of Experience
55,000 Employees
134K-162K Annually
5-7 Years of Experience
Fintech • Machine Learning • Payments • Software • Financial Services
Seeking a Senior Platform Engineer with experience in Workday to support Human Resource technology at Capital One. Responsibilities include developing highly-resilient objects, championing automation, and delivering solutions across various HR functions. Must have at least 4 years of Workday experience and proficiency in functional configuration tasks.
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8 Days Ago
Richmond, VA, USA
Hybrid
55,000 Employees
291K-389K Annually
7+ Years of Experience
55,000 Employees
291K-389K Annually
7+ Years of Experience
Fintech • Machine Learning • Payments • Software • Financial Services
Senior Distinguished Engineers at Capital One are deep technical experts and thought leaders who accelerate adoption of engineering practices, collaborate on tough issues, mentor technical expertise, and promote engineering excellence.
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8 Days Ago
Richmond, VA, USA
Hybrid
55,000 Employees
235K-268K Annually
3-5 Years of Experience
55,000 Employees
235K-268K Annually
3-5 Years of Experience
Fintech • Machine Learning • Payments • Software • Financial Services
As a Senior Lead Machine Learning Engineer at Capital One, you will be responsible for designing, building, and delivering machine learning models and components to solve real-world business problems. You will collaborate with cross-functional teams to enhance software for big data and ML applications, retrain and maintain models in production, and ensure high availability and performance of machine learning applications.
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