Top Senior Level Data & Analytics Jobs

The Fraud Technologist will lead teams in developing and implementing fraud detection and prevention strategies for clients. Responsibilities include project management, mentoring staff, and delivering enterprise-wide solutions while optimizing business performance through data-driven insights.

As a Fraud Technologist Manager, you will lead the Financial Crimes Data and Analytics team, driving fraud transformation initiatives through strategic consulting and delivery on client projects. Responsibilities include overseeing project execution, mentoring junior staff, and developing enterprise-wide fraud detection and prevention solutions, while fostering a collaborative team environment.

Lead and manage end-to-end fraud transformation projects at client organizations, mentoring junior staff and delivering enterprise-wide fraud detection solutions. Responsible for consulting on strategy and technology architecture related to fraud prevention.

The Sr. Data Engineer will build and maintain data pipelines, collaborate with cross-functional teams to understand data needs, and implement process improvements for better data delivery in a cloud-based environment. This role involves managing data engineering projects and ensuring scalable analytics applications.

As a Senior Applied Scientist at Chewy, you'll leverage machine learning and data science to enhance product discovery and optimize advertising solutions. Responsibilities include deploying models, collaborating with product and engineering teams, leading model development, publishing research, mentoring junior scientists, and communicating insights to leadership.

The Senior Data Engineer (Data Engineer III) at Chewy will be responsible for designing and optimizing data systems, managing data integration and SSOT tables, providing leadership and mentorship, evaluating innovative solutions, and collaborating with strategic partners. The role requires a Bachelor's or Master's degree in a related field, at least 5 years of experience in data engineering, expertise in SQL and Python, and proven leadership and communication skills.

The Principal, CX Analytics & Insights will analyze Voice of the Consumer data trends, provide actionable insights to improve business strategies, prepare reports for executive meetings, and collaborate with cross-functional teams to drive consumer excellence initiatives.

The Sr. Workday Analyst is responsible for designing, implementing, maintaining, and supporting Workday modules, optimizing system processes, providing data reporting support, resolving technical issues, and ensuring system adoption across HR. The role includes vendor management and compliance with operational guidelines.

The Sr. Workday Analyst will design, implement, and support Workday modules, enhance system accuracy and efficiency, provide data reporting, resolve Workday and Kronos escalations, train HR staff, and collaborate with HR partners to meet system requirements.

The Senior Architect will guide clients in developing Big Data strategies, focusing on DataBricks, while designing data flows and processing pipelines using modern tools. Responsibilities include platform selection, data management expertise, coaching consultants, ensuring data integrity, and coordinating with application owners to integrate analytics platforms.

The Senior Architect will lead data engineering and analytics initiatives, providing guidance on DataBricks, designing data processing pipelines using modern tools like Spark on Scala, Flume, and more. Responsibilities include data architecture evaluation, coaching consultants, ensuring data integrity, and attending necessary meetings for technical development.

The Senior Architect will lead the development of Big Data strategies, focusing on DataBricks and designing data pipelines for analysis using modern tools. Responsibilities include data architecture, platform selection, providing data management expertise, guiding team members, and ensuring data integrity while collaborating with application owners.

As a Senior Machine Learning Engineer, you will design data pipelines, develop machine learning models, and collaborate with various teams to integrate ML capabilities into products. You will also train others, conduct experiments to validate outcomes, and serve as a thought leader in data-driven innovations.