Top Remote Senior Level Data & Analytics Jobs
As a Senior Data Analyst, you will analyze digital performance data, improving customer engagement and conversion rates. Your role includes monitoring KPIs, creating dashboards, providing insights based on marketing metrics, and collaborating across teams to support data-driven decision-making.
The Senior Data Engineer is responsible for analyzing existing data sets, defining data requirements, and performing statistical modeling to improve decision-making processes. Key responsibilities include managing projects, coaching lower-level professionals, developing reports using SQL, and delivering analytic solutions while ensuring data quality and compliance with development standards.
The Senior Consultant provides consulting services for Epic-related projects, focusing on system build, troubleshooting, and optimizing workflows for clients. Responsibilities include mentoring project teams, documenting risks, and working closely with Epic end users and project leaders to ensure project success.
The Senior Consultant - Staffing Services focuses on delivering expert services by evaluating client systems, developing workflows, providing technical expertise, and leading project management efforts while ensuring alignment with client goals.
The Senior Database Administrator and Performance Engineer will oversee the performance, availability, and restorability of database servers for SaaS applications in AWS. Responsibilities include monitoring transactions, optimizing indexes, troubleshooting performance issues, collaborating on database design, and ensuring data durability and integrity through effective backup and recovery processes.
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The Senior Systems Analyst will optimize Vital Farms' Record to Report functions by planning, designing, implementing, and supporting related systems. Responsibilities include defining requirements, application configuration, user training, and enhancing business processes in collaboration with stakeholders.
As a Staff Data Engineer, you will lead the evolution of the CS Data Platform, building and maintaining data pipelines and APIs, collaborating with cross-functional teams to improve data handling capabilities for AI-driven customer support solutions.
As a Staff/Senior Staff Data Engineer at Valo Health, you will lead the development of complex data transformation initiatives, integrating real-world data into analysis-ready products, while collaborating with scientists and engineers. Responsibilities include building data pipelines, maintaining data quality, and providing technical leadership within the data engineering team.
As a Staff Machine Learning Data Scientist, you will lead the development of machine learning tools for patient data, integrating insights from diverse stakeholders, and conducting complex analyses in cloud environments. You'll collaborate with experts to provide innovative solutions and generate novel clinical insights from extensive patient data.
The Principal Data Privacy Consultant will assess compliance with data privacy regulations, develop privacy policies and documentation, conduct gap and maturity assessments, and provide advisory services to clients. This role involves mentoring colleagues and contributing to the growth of the data privacy consulting practice.
The Lead IT Data Scientist will design and develop scalable AI and machine learning solutions, conduct research, and utilize big data tools to enhance health outcomes. Responsibilities include leading model development, data analysis for business decisions, ensuring data quality, and deploying models with CI/CD practices. The role requires collaboration with internal customers to meet AI/ML needs and communicating findings to non-technical partners.
The Lead Database Engineer will design, implement, and maintain critical PostgreSQL database systems for a 24x7 SaaS platform, ensure database operations support business needs, mentor team members, and comply with HIPAA policies.
The Staff Engineer will lead the design and development of GenAI-powered product capabilities, driving technical delivery through the feature lifecycle. Responsibilities include identifying opportunities for AI/ML applications, collaborating across teams, owning service uptime, and developing automation and microservices.
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