Jobs at Tiger Analytics

The Data Engineer will architect and implement advanced analytics capabilities, manage data pipelines, and optimize data processing using AWS cloud and various analytical tools.

The Machine Learning Engineer will create scalable ML systems, build production data pipelines, and ensure robust deployment and monitoring of solutions.

Seeking an experienced Data Engineer to design and maintain data pipelines and infrastructure, collaborating with data scientists and stakeholders.

Manage large-scale data analytics engagements, collaborate with technology teams, and present solutions to stakeholders to drive business value.

The role involves engaging with client teams to gather and analyze requirements, managing projects, acting as a point of contact, and collaborating with offshore teams to deliver analytical solutions.

The Manager, BI Consulting will lead BI initiatives, engage stakeholders, analyze requirements, design data solutions, and manage client relationships.

The Data Product Manager will lead the development of enterprise data products by translating business needs into scalable data solutions, managing analytics projects, and coordinating with global teams to ensure efficient delivery and optimization of data initiatives.

Manage end-to-end talent acquisition for data science and analytics roles, collaborating with stakeholders and maintaining candidate pipelines. Build partnerships with external firms.

Lead analytics consulting engagements: translate business problems into end-to-end data science and ML solutions, present to executive stakeholders, manage projects and global teams, and operationalize analytic outputs with IT and data engineering.

Looking for a Data Engineer experienced in Dataiku to design and maintain data pipelines and infrastructure, ensuring data flow and integration across teams.

Consultants at Tiger Analytics design analytics solutions for clients, manage projects, and engage stakeholders to translate business problems into actionable insights.

Design, build, and deploy scalable ML solutions using GCP and Vertex AI. Collaborate with teams to operationalize models and monitor performance.

The GenAI Engineer will design, build, and deploy Generative AI solutions, focusing on reinforcement learning and multi-agent workflows, while collaborating with various teams to enhance model performance.

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.

As a Senior Agentic AI Engineer, you will lead innovation in AI initiatives, from ideation to prototyping, collaborating with teams to deliver impactful solutions.

As a Machine Learning Engineer, you'll develop scalable ML solutions using Google Cloud Platform and Vertex AI, collaborate with teams, and operationalize models from ingestion to monitoring.

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

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.