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As a Data Analyst in the Growth Strategy & Analytics team at Lyft, you will manage and analyze experiments, develop dashboards to monitor performance, and partner with stakeholders to translate analytical insights into actionable strategies, contributing to sustainable growth through data-driven decision-making.
The Senior Data Analyst will lead management and experimentation for key acquisition levers at Lyft, focusing on optimizing growth strategies. Responsibilities include developing dashboards, analyzing data for performance insights, and collaborating with stakeholders to translate findings into actionable plans. Key requirements include strong analytical skills, experience in a high-growth environment, and proficiency in SQL.
The Data Science Manager will lead a team of Data Analysts within the P&L management team at Lyft, focusing on managing the profit and loss for the Rideshare business. Responsibilities include mentoring the team, analyzing business problems using data analytics, collaborating with Data Scientists and Engineers, and presenting insights to senior leadership to influence investment strategies.
The role involves designing and building data infrastructure, developing data pipelines, and transforming data to provide actionable insights. Responsibilities also include guiding teams through complex decisions, improving data architecture, and ensuring compliance with governance policies while collaborating with stakeholders.
The Consultant will analyze and optimize client processes, lead change management efforts, and develop solutions for process improvements. Responsibilities include managing process initiatives, creating are artifacts such as process maps, mentoring team members, and developing KPIs to track performance during and after implementation.
The Head of Data & Analytics will own the data stack, drive insights, and partner with product, engineering, and operations teams. Responsibilities include developing analytics capabilities, building dashboards, owning the data science roadmap, and ensuring data-driven decision-making across the organization.
The role involves providing cybersecurity data analysis services, maintaining and supporting SIEM systems, ensuring service availability, managing configurations, and deploying updates and emergency maintenance actions for security measures.
The Cybersecurity Operations Specialist will perform cybersecurity data analysis, manage SIEM systems, ensure service availability, execute maintenance actions, and improve system performance. They will also handle the onboarding of IT resources and manage security event routing to mission partners.
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The Data Analytics Applications Engineer will work on Data Management and Data Pipeline projects, utilizing tools like Pig and Py-Spark, with a preference for those familiar with NiFi and Pressurewave. Candidates are required to have significant experience depending on their educational background.
The Senior Data Engineer at Bank of America is responsible for developing and implementing analytics and automation solutions, handling complex data sets, building data pipelines, and ensuring data management standards. This role involves collaboration with audit and technology teams, mentoring, and contributing to test suites.
The Data Analytics Platform Engineer role involves designing and delivering data analytics services, implementing cloud architectures, and modernizing platform solutions. The engineer will work with big data technologies and lead efforts in platform optimization while ensuring high availability and disaster recovery.
The Data Analytics Analyst will maintain and run existing analytics and data ETL processes, troubleshoot data issues, collaborate on new product development, and document processes while engaging with internal and external stakeholders. Responsibilities include monthly reporting, project management, and researching best practices for operational enhancements.
Seeking a Fund Analytics & Operations Associate to contribute to trading operations, handle trade processing, investigate trade breaks, and provide analytics for decision-making. Responsibilities include improving procedures, analyzing data, and collaborating with internal teams. Bachelor's degree required. Must be fully vaccinated against COVID-19.
The Senior Lead Data Analytics Platform Engineer will design and optimize a high-performance data analytics platform, focusing on scalable data systems and cloud-native architectures. Responsibilities include leading teams, optimizing data pipelines, ensuring data quality, implementing best practices in data governance, and driving innovation in data engineering processes.
The Sr. Director of Data Analytics will lead a team to develop data-driven analytic solutions that drive business growth, focusing on areas such as product planning, customer insights, and operations. The role involves consulting with stakeholders, creating dashboards, and improving analytics practices within the organization.
The Senior Engineer - Data Analytics at GEICO will develop high-performance data analytics solutions, utilizing programming languages and reporting tools to transform large datasets. Responsibilities include mentoring engineers, leading design sessions, managing deployment pipelines, and ensuring data quality and visualization to support business decisions.
As a Senior Product and Solutions Consultant, you will lead the design and implementation of data visualization solutions using Elastic Stack, oversee the development process, and ensure seamless integration with Genesys platforms. Your role involves managing the full lifecycle of implementations, focusing on user requirements to enhance customer engagement and operational efficiency.
As a Data Scientist at Twitch, you will define and track KPIs, design experiments, implement data instrumentation, and evaluate product impact. You will inform product strategies and lead analyses to support decision-making across the Creator product team, focusing on creator and viewer behavior.
As the Director of Data and Analytics at Nutrabolt, you will lead the consumer insights team, develop marketing analytics capabilities, and drive optimization of marketing investments through data-driven insights, collaboration, and effective decision-making.
As a Sales Representative for CoStar, you will manage relationships with existing clients and prospect new ones, promoting CoStar and LoopNet products. Responsibilities include understanding client needs, conducting product demonstrations, and overseeing the full sales cycle from prospecting to closing. You will receive extensive training and have access to a plethora of qualified leads to support your sales efforts.
The Data Scientist will collaborate with Product and Engineering teams to enhance testing and reporting capabilities, support A/B testing, quantify product efficacy, and provide actionable insights to business leads, while developing Tableau dashboards for visualizations.
Oversee and support Data & Analytics capabilities across Mattel's Direct to Consumer and e-commerce organization. Drive digital transformation using insights to inform marketing strategies, manage a team of data experts, and establish a data governance framework for the DTC business.
This role involves designing and developing data solutions, creating data pipelines, and facilitating client decision-making by transforming raw data into insights. As a senior manager, responsibilities include leading data architecture strategies, mentoring teams, and ensuring compliance with data governance policies.
This role involves leading the design and development of robust data solutions, managing data infrastructure, and transforming raw data into actionable insights. Responsibilities include developing data pipelines, coaching teams, and solving complex data challenges while ensuring compliance with governance standards.
The Data Analytics Manager will oversee data analysis and the design of analytics products for Nike, translating complex business requirements into clear data requirements. This role involves extensive data profiling, modernization of data architecture, documentation, and training users on data products, while adhering to best practices in data integrity and analysis.
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