Top Data & Analytics Jobs

The Senior Manager of Machine Learning Engineering at Capital One will lead a team to design, develop, implement, and optimize machine learning applications. This role involves collaborating with Product and Data Science teams, ensuring high performance of ML systems, constructing data pipelines, and managing code quality. The position focuses on adopting best practices in machine learning and delivering optimized solutions at scale.

The Machine Learning Ops Developer IV is responsible for developing and supporting high-performance Machine-Learning batch processing code, troubleshooting, maintaining system workflows, orchestrating AWS processes, and mentoring junior developers while actively collaborating with cross-functional teams to enhance service quality and reliability.

As a Senior Associate in Applied AI/ML, you will develop and implement data science solutions to complex business problems, engage with stakeholders, and mentor team members. Responsibilities include data analysis, modeling, and optimizing AI/ML solutions for strategic projects across the firm.

As an Applied AI ML Senior Associate, you will apply advanced analytics and critical thinking skills to solve complex business problems across Marketing, Finance, and Operations. Your responsibilities will include developing machine learning and optimization models, performing statistical analysis of large datasets, and communicating insights to stakeholders. You will also act as a subject matter expert and foster a continuous learning environment.

As an Applied AI Modeling Lead, you will develop high-impact quantitative models for financial needs, oversee modeling engagements, provide expertise to business partners, conduct data analysis, and mentor junior staff.

As a Senior Machine Learning Engineer, you will design, develop, and deploy advanced computer vision models for applications like object detection and video analytics. You will optimize models for performance, mentor junior members, and collaborate with cross-functional teams to deliver scalable end-to-end solutions.

In this role, you will design, build, and maintain machine learning applications, collaborating with cross-functional teams to deliver optimized models at scale. You will focus on ML infrastructure, model training, hyperparameter tuning, and ensuring high availability of applications. Leadership and direction for team development will be essential, along with working in an Agile environment.

As an Applied AI/ML Data Scientist, you will innovate investment banking through AI and data analytics, develop machine learning systems, analyze complex datasets, and present insights to stakeholders. You'll collaborate with a diverse team to push the boundaries of financial technology.

As a Principal Data Scientist at Self Financial, you'll lead efforts in leveraging machine learning and data analytics to develop innovative solutions and models that aid in financial inclusion. Your role will involve feature engineering, collaborating across teams on product development, and establishing data science standards, ultimately impacting millions of customers' financial wellbeing.

As a hands-on Data Science Manager, you will lead a team to develop advanced machine learning models focused on credit risk and lending. You will oversee the deployment of innovative solutions, collaborating across departments to enhance financial inclusivity and improve credit assessment accuracy, while managing a cross-functional team and driving strategic initiatives.

The Senior Machine Learning Engineer at Capital One will design and implement machine learning models and systems, collaborate with cross-functional teams, optimize ML applications, and ensure high performance and availability of deployment. Responsibilities include data pipeline construction, ML model monitoring, and leveraging cloud technologies.

As a Principal Software Engineer in AI/ML Integrations, you will design, develop, and deploy AI & ML integration pipelines within the elluminate platform. Collaborate with data science teams to streamline data management and analytics for clinical trials, while ensuring scalability, performance, and security. Contribute to architectural decisions and mentor junior engineers in a collaborative environment.

In this role, you will build and evolve an AI platform by developing next-generation Large Language Models for enterprise applications. Responsibilities include applying ML methods to real-world problems, conducting LLM benchmarking, data collection, collaborating with cross-functional teams, and contributing to innovative developments and research publications.

The Senior Machine Learning Engineer at Capital One will design, develop, and implement machine learning applications in an Agile environment. Responsibilities include collaborating with product and data teams, constructing optimized pipelines, and deploying models to ensure high performance and availability. The role also involves maintaining and monitoring models in production and upholding best practices in ML development.

The Principal Data Scientist will lead the development of machine learning models to enhance customer experiences and anticipate needs across Capital One's digital products. Responsibilities include data exploration, model building, and collaboration with business teams to improve outcomes in marketing and fraud prevention.

As a Principal Data Scientist in Consumer Identity Machine Learning, you'll explore customer behavior patterns, develop real-time machine learning models, and ensure data accuracy to enhance customer experiences. You'll lead all phases of model development in collaboration with engineering and business teams, focusing on data-driven insights over vast datasets.

The Principal Data Scientist in Consumer Identity ML utilizes data science and machine learning to enhance customer experiences at Capital One. Responsibilities include developing real-time models, exploring customer behavior patterns, improving operationalization of production systems, and partnering with product teams to innovate solutions across digital platforms while ensuring data accuracy and fraud prevention.