Jobs at Tiger Analytics

The Technology Partner will lead technology solutions and data transformation initiatives for Fortune 100 clients, providing thought leadership and managing executive relationships.

The Databricks Architect will design and implement data architecture solutions using Databricks, AWS, and Snowflake, focusing on MLOps and data governance.

The Gen AI Data Engineer will design and build distributed data systems, develop data pipelines, manage data infrastructure, and integrate technologies for real-time and batch processing, contributing to scalable analytics solutions.

Design and lead the development of cloud-native Generative AI platforms and solutions, ensuring scalability, security, and integration with enterprise applications.

The Senior Data Scientist will design and deploy time-series forecasting models, collaborate with stakeholders, and operationalize models in cloud environments, focusing on demand planning across various industries.

The Agentic AI Engineer is responsible for deploying, executing, and improving Machine Learning solutions, creating scalable systems, and collaborating with teams to drive strategy and business value through analytics.

Lead business development and growth in AI/ML, provide technical leadership in data science solutions, and enhance client engagement by delivering strategic data insights.

The Sales Director will develop and execute sales strategies for consulting services, manage relationships with technology partners, and grow the client base for Tiger Analytics.

The Finance Director will lead the finance team, overseeing financial planning, analysis, and management practices to support the company's growth and performance optimization.

Lead modernization and design of applications, architecting cloud-native systems, optimizing APIs, and ensuring security and scalability for enterprise applications.

The Databricks Architect will design and implement large-scale data solutions, optimizing performance and reliability, while leading initiatives in data engineering.

The Machine Learning Engineer will develop software solutions, optimize data pipelines, and deploy machine learning models using cloud platforms and best practices.

The Senior Data Scientist will analyze manufacturing data to improve quality and optimize processes through advanced analytics, with a focus on driving cost and waste reduction.