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As a Senior Data Scientist at Tiger Analytics, you will apply your expertise in AI, machine learning, and generative AI to design and build advanced analytics solutions. This role involves collaboration with cross-functional teams to address technical challenges, evaluate and enhance generative AI models, and engineer features from diverse data sources while contributing to the development of best practices in data science.
The Technical Project Manager will manage and oversee project-related activities, ensuring timely delivery and desired outcomes. Responsibilities include developing project plans, managing timelines, coordinating with teams across various disciplines, and utilizing Agile methodologies to guide product roadmaps and manage backlogs.
The Manager/Senior Manager in Technology Consulting at Tiger Analytics will manage large-scale data analytics client engagements, collaborating with technology and program teams, presenting solutions, and overseeing project implementation. Responsibilities include understanding business requirements, managing senior client stakeholders, and developing analytics solutions leveraging modern technologies.
The Data Science Manager will lead the Pricing and Promotion Optimization team to develop strategies enhancing pricing initiatives. Responsibilities include roadmap development, quarterly planning, team leadership, stakeholder collaboration, and market analysis, while mentoring data scientists and ensuring alignment with business goals.
The Data Product Manager will translate business problems into analytics solutions, manage analytics projects, and communicate insights to stakeholders. Responsibilities include developing end-to-end analytics solutions, overseeing data management within the Enterprise Data Foundation, and building data roadmaps for global initiatives.
As a Data Engineer at Tiger Analytics, you will design, build, and maintain data pipelines and infrastructure, supporting data integration and collaboration with data scientists and analysts to facilitate data-driven decision making.
The BI Senior Manager will lead the development of enterprise BI and dashboard initiatives by engaging with stakeholders, analyzing requirements, ensuring data architecture meets business needs, building dashboards, managing client issues, and ensuring data quality while collaborating with cross-functional teams.
The Data Engineer will design databases, manage complex data sets, and develop self-service dashboards. They will apply analytical skills to derive insights for solving business problems and enhance data analytics capabilities within the company.
The Data Architect will design and implement data solutions tailored to complex business needs, focusing on Snowflake architecture. Responsibilities include developing data blueprints, optimizing performance, ensuring data governance, and collaborating with stakeholders for technical specifications and data integration.
As a Senior Data Engineer, you'll design, build, and maintain scalable data pipelines in cloud infrastructure, collaborating with teams for data analytics and machine learning projects. Your role includes developing ETL pipelines, optimizing SQL performance, and working with both relational and NoSQL databases.
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