Top Data & Analytics Jobs

As a Principal Quantitative Modeler, you will enhance modeling frameworks, develop econometric and machine learning models, and provide insights for Capital One's risk and capital needs. Collaborate across teams to create analytical solutions and communicate results effectively to drive business performance.

The Executive Director of Data Engineering and Governance will lead data engineers and governance analysts in designing and overseeing technology architecture for data management. Responsibilities include implementing data governance frameworks, managing data quality processes, and collaborating with data owners to establish critical data elements. This role also involves directing the use of AI and machine learning for data cleansing and organization, while aligning technical solutions with business strategy and goals.

The Executive Director, Data Engineering & Data Governance will lead a team of data engineers and analysts to develop and implement technology solutions for data management and governance. Responsibilities include establishing data quality processes, building data structures, and using AI and machine learning to enhance data handling. This role also involves cross-functional collaboration, project management, and development of business strategies to improve operational efficiency.

The Senior Machine Learning Engineer will design and build services for ML modelers, integrate data streams to create efficient models, and lead MLOps initiatives. The role involves collaborating with various teams to enhance ML tools and infrastructure while maintaining production software and developing new solutions.

The Senior Machine Learning Engineer will focus on utilizing machine learning technologies to develop risk-based solutions that enhance customer verification processes and reduce fraudulent identities. Responsibilities include designing ML pipelines, maintaining model platforms, and shaping long-term ML strategies while collaborating with various teams at Cash App.

The role requires leading the Credit and Data Science functions for Empower's international operations, developing risk models and credit policies, and launching innovative products to improve customer financial outcomes. The candidate will lead teams to analyze consumer behaviors and tailor solutions for different markets, contributing to business growth in Latin America and South East Asia.

Lead Credit and Data Science functions for international markets. Develop risk models, credit policies, and innovative products to enhance customer experience and business growth. Collaborate with teams to adapt strategies based on market-specific data and consumer behavior.

As a Staff Data Scientist at Empower, you will develop risk models and credit policies to drive competitive underwriting practices. You will lead teams to analyze consumer behaviors and adapt solutions for the Latin American market, enhancing customer financial well-being. This role is pivotal for launching innovative financial products and requires tackling complex geographic challenges.

The Staff Data Scientist is responsible for developing and implementing machine learning models and analytics to drive business growth and improve customer financial situations. This role requires close collaboration with product, tech, and finance teams, and involves the entire model development process from conception to deployment, focusing on credit risk models to enhance approval rates and reduce loss rates.

As a Software Engineer in the Core Machine Learning team, you will deploy machine learning models, enhance infrastructure for new use cases, and create scalable design patterns for safe model deployment. You will collaborate with machine learning engineers to optimize backend services while driving initiatives and methodologies for scalable machine learning solutions.

As an Applied AI/ML Lead, you will spearhead large AI/ML initiatives, collaborate with various teams to develop and implement machine learning models, especially for NLP and generative AI applications. You will manage the end-to-end machine learning pipeline and ensure the alignment of technical solutions with business needs, requiring strong communication and leadership skills.

The Sr. Manager will lead R&D teams to develop driver behavior detection algorithms from smartphone sensor data for Arity. Responsibilities include setting a vision for machine learning applications, aligning with product and engineering teams, and managing diverse data science teams while ensuring successful model deployment and strategic development.

As a Senior Data Scientist at Spring Health, you will work with the Customer Experience team to build data products, analyze member mental health journeys, and provide actionable insights to enhance customer satisfaction and product value. Your role involves collaborating with internal teams and implementing AI/ML capabilities to improve mental health care solutions.

As a Senior Business Analyst, you will apply your strategic and analytical skills to solve complex problems across machine learning platforms and generative AI, collaborating with business partners and cross-functional teams, evaluating AI and ML opportunities, and developing dashboards to track value creation.

As a Senior Director of Technical Program Management at Capital One, you will lead initiatives enhancing data management and machine learning capabilities. You will oversee complex technical projects, ensure delivery of solutions, and foster collaboration across teams. Your role involves shaping TPM practices while aligning projects with business objectives and mitigating technical risks.

As a Principal Data Scientist, you will lead the development of machine learning models, conduct research on emerging technologies, and collaborate with teams to enhance customer experiences and business outcomes at Capital One. You will also engage in data analysis and operationalize models for large-scale production systems.

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.