Jobs at Tiger Analytics

Design, train, and deploy ML solutions with emphasis on generative AI and NLP (LLMs, RAG). Work with cross-functional teams to analyze text/transcription data, build scalable models, evaluate new algorithms, document results, and present findings to stakeholders to drive business value.

Lead delivery of AI and analytics solutions for a financial services client: manage end-to-end projects, run discovery workshops, translate requirements into product roadmaps, assess Agentic AI vs rules-based approaches, align Databricks Lakehouse and Unity Catalog architectures, and coordinate stakeholders and hybrid delivery teams.

The Forward Deployment Engineer will deploy and optimize Generative AI solutions, architect scalable infrastructure, and implement data pipelines across multi-cloud environments while collaborating with cross-functional teams to maximize business value.

The Forward Deployment Engineer will deploy and optimize Generative AI solutions on-site, collaborating with engineering teams to operationalize AI systems across multi-cloud platforms.

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.

This role leads Revenue Growth Management initiatives, linking data analytics with executive strategy to drive business growth through actionable insights and project management.

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

Lead Tableau data visualization strategy: design and optimize high-performance dashboards, establish governance and best practices, mentor teams, enable adoption, and partner with data teams for robust models and performance.

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

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 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.

Lead portfolio-level Data & AI strategy and technical governance for enterprise clients. Advise C-suite, drive architecture and modern data stacks, win high-value engagements, and scale engineering and data science teams.

Lead design and governance of enterprise ontologies, knowledge graph architecture, ingestion pipelines, and semantic layers. Enable semantic interoperability across data products, implement inference and reasoning, and establish standards, versioning, and data contracts to support scalable graph-driven analytics and AI augmentation.

The FP&A Leader will analyze financial data, support strategic decision-making, and prepare reports for senior management at Tiger Analytics.

Define enterprise AI strategy and architecture for LLMs, RAG, and predictive models; design secure, high-performance REST/GraphQL APIs and event-driven systems; establish AI/data governance; and lead cross-functional teams to productionize real-time AI applications.

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