Top Remote Data & Analytics Jobs in Seattle, WA

The Senior Analytics Engineer designs and optimizes data systems using Snowflake and dbt. Responsibilities include collaborating with sales, marketing, and finance analytics teams, developing data models, overseeing dbt projects, analyzing product performance, building financial models, and maintaining data quality and governance.

As a Lead Compliance Analyst, you will conduct branch office inspections using risk-based testing methodologies to ensure compliance with FINRA and state insurance laws. Responsibilities include developing inspection plans, analyzing data, and delivering results to partners, while maintaining compliance and identifying risk exposures.

The Data Scientist will develop the data analytic and research functions, build data operations systems, maintain ETL processes, and collaborate with technology and product teams to support organizational priorities. This role focuses on enhancing college admissions access and equity through data-driven insights and products.

As a Data Engineer at Nascent, you will manage the entire data pipeline that supports trading models, ensuring data cleanliness and access for researchers. You'll automate data collection, build and maintain APIs, and develop tools for efficient data querying in a high-stakes environment, while collaborating closely with Portfolio Managers.

The Senior Data Scientist will architect, design, and implement generative AI models for ASR and TTS applications, leveraging LLMs. Responsibilities include training and optimizing models, collaborating with cross-functional teams, and innovating existing models while staying updated on the latest advancements in generative AI.

The Senior Revenue Cycle Operations Analyst ensures cash integrity for healthcare services, oversees accounts receivable accuracy, manages payment posting and audits, develops procedures, and collaborates with the Finance team and external vendors to optimize revenue cycle operations.

The Head of Data will lead data-driven decision-making, oversee product data science and analytics, and collaborate closely with data engineers and scientists to enhance monetization, engagement, and retention. This role emphasizes hands-on involvement in problem-solving within a modern data stack, ensuring a world-class learning experience for customers.