Top Data & Analytics Jobs in Seattle, WA
Looking for a Data Scientist to join the Risk Data Science and Analytics Team at Square. Responsibilities include improving risk controls, managing core operational metrics, advising senior stakeholders, building processes to root out high-risk activity, and preventing fraud. Key tasks involve diagnosing problems, designing experiments, developing data pipelines, and partnering with cross-functional teams to develop solutions. Qualifications include a degree in a quantitative/technical field, 8+ years of experience, proficiency in SQL, Python, and Looker, strong statistics knowledge, and experience with machine learning model development.
Partners with Consumer and Ecommerce Business Groups to ensure delivery of applications aligned to the business and IT strategy, as well as the support of applications in B2B and B2C areas. Responsible for authoring data integrations and API related Consumer business requirements for CrowdStrike. Collaborates with business users to develop use cases and provides inputs into business processes based on design capabilities.
Senior UI Engineer role focusing on building nextgen data visualization framework for CrowdStrike. Responsibilities include executing front-end data visualization strategy, designing single page application framework, collaborating with multidisciplinary teams, and ensuring code quality. Required skills in D3.js, HTML5, CSS, Javascript, RESTful API, GraphQL, Typescript, Ember CLI, Node/NPM, Webpack, Responsive UI, Vega-Lite, HighCharts, amCharts, Ember, React, Angular, Vue, Tailwind, CI/CD.
Seeking a Cloud Security Competitive Intelligence Analyst with 5+ years of experience in the cloud security market. Responsibilities include providing field guidance, analyzing market trends, developing competitive strategies, and working closely with product and sales teams.
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You will be at the forefront of developing and implementing advanced ML models to address complex challenges and contribute to our business goals.
Featured Jobs
Looking for a Data Scientist to join the Risk Data Science and Analytics Team, responsible for improving risk controls through advanced statistical and analytical techniques, managing core operational metrics, and advising senior stakeholders on Risk controls.
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Key strategic business partner collaborating with Product Managers and senior stakeholders. Optimizing gross margins, developing financial models, ensuring royalty allocations, responsible for data visualization. Master's degree required. Must have extensive experience in SQL, Python, Spark, and related tools.
The Database Manager is responsible for executing the day-to-day support, maintenance, and improvement of the organization's CRM systems and related data.
The Director of Performance Reporting, Business Analytics & Insights at Pfizer works with senior business stakeholders to drive performance tracking and reporting for commercial performance, standardize reporting processes, and generate insights to support decision-making. This role is highly collaborative, covering a broad range of strategic topics critical to the business, and involves thought leadership, research capabilities, and effective communication of complex information.
Seeking a Program Manager, Training to serve as the owner of the Data/AI learning portfolio, collaborating with internal and external subject matter experts to develop and manage training programs for upskilling needs in data management, analysis, and AI technologies.
Join Chewy as a Data Engineer II on the Transportation Systems team. Own the design, development, and maintenance of enterprise data pipelines, create data products for analytics, and lead the evaluation of emerging tools and processes for analytics. Requires 5+ years of experience and expertise in data engineering with skills in Python, SQL, Spark, and more.
Dropbox is seeking a Data Engineer to join the Finance Data Engineering team. The role involves building financial data pipelines, curating datasets, and providing data for business use. Responsibilities include managing data pipelines, ensuring data quality, solving integration problems, and collaborating with business and engineering teams.
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