
1001 - 5000 employees
Founded 2011
🤖 Artificial Intelligence
🤝 B2B
Artificial Intelligence • B2B • Consulting
Tiger Analytics is a leading AI and analytics consulting firm that specializes in leveraging data science and machine learning to provide strategic business insights across various industries. They offer services in data strategy, AI engineering, and business intelligence to enable data-driven decision-making and digital transformation for their clients. Tiger Analytics collaborates with top technology partners like Microsoft, Google Cloud, and AWS to deliver cutting-edge solutions. They serve a diverse range of sectors including consumer packaged goods, healthcare, and finance, helping businesses operationalize insights and differentiate with AI and machine learning technologies.
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1001 - 5000 employees
Founded 2011
🤖 Artificial Intelligence
🤝 B2B
Artificial Intelligence • B2B • Consulting
Tiger Analytics is a leading AI and analytics consulting firm that specializes in leveraging data science and machine learning to provide strategic business insights across various industries. They offer services in data strategy, AI engineering, and business intelligence to enable data-driven decision-making and digital transformation for their clients. Tiger Analytics collaborates with top technology partners like Microsoft, Google Cloud, and AWS to deliver cutting-edge solutions. They serve a diverse range of sectors including consumer packaged goods, healthcare, and finance, helping businesses operationalize insights and differentiate with AI and machine learning technologies.
• Design Databricks-driven enterprise data warehousing (EDW), lakehouse, and business intelligence (BI) systems. • Build scalable pipelines using Azure Hub, Device SDK, DPS, and Stream Analytics. • Implement information lifecycle management (ILM) from data ingestion to archiving. • Define, build, and enforce global data governance and master data management practices. • Extract and manipulate unstructured data into connected datasets for advanced analytics.
• Core Cloud Data Platform (Must Have) • Databricks: Strong proficiency in building optimized spark pipelines, delta lakes, and lakehouses. • Cloud Ecosystem (Option A: Azure Suite) • IoT Infrastructure: Azure Hub, Device SDK, Device Provisioning Services (DPS), and Device Twins. • Compute & Storage: Azure Functions, Cosmos DB, and Azure Stream Analytics. • Cloud Ecosystem (Option B: AWS Alternative) • IoT Infrastructure: AWS IoT Core, IoT Device Management, and IoT Device Defender. • Compute & Storage: AWS Lambda, DynamoDB, Amazon Kinesis, and EMR. • Data Engineering & Governance • BI & EDW: Deep expertise in enterprise data warehousing and business intelligence tools. • Data Modeling: Proven ability to manage both structured and unstructured data assets. • Good to have-Experience in architecting and building Azure IoT platforms/apps with good exposure to containerization and server less architecture.
• Significant career development opportunities exist as the company grows. • Unique opportunity to be part of a small, challenging, and entrepreneurial environment. • High degree of individual responsibility. • Equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.
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