Jobs at Tiger 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 Leader drives revenue growth by managing strategic client relationships, leading presales activities, and winning multi-million-dollar Quality Engineering deals.

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.

The Data Engineering Lead will develop and deploy complex data infrastructure, ensuring high-quality data availability for analytics and AI initiatives.

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 Full Stack Gen AI Engineer will build high-performance API services, implement Generative AI architectures, and manage AWS infrastructure and DevOps workflows.

The Senior Data Scientist will optimize algorithms and employ advanced analytics for pricing in the supply chain, collaborating with teams and driving innovation.

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.

Embed with client engineering teams to operationalize LLMs and retrieval systems across multi-cloud environments. Build agentic solutions using Vertex AI Agent Builder and ADK, connect agents securely to BigQuery/Spanner via MCP, implement streaming pipelines (Dataflow) for real-time inference, and manage model training, tuning, deployment, and evaluation on Vertex AI. Provide consultative guidance, cross-functional collaboration, and clear stakeholder communication to ensure business value from Generative AI solutions.

Lead client relationships, delivery, and account growth for analytics engagements. Define analytics roadmaps, scale pilots to long-term programs, present to executives, collaborate with sales, and manage teams solving CPG, Retail, and financial services problems using data science and ML.

Partner with senior leaders to drive workforce planning, talent and performance management, PIP governance, HR analytics, employee relations, retention and succession planning, policy and compliance, and culture and change initiatives supporting North America-based employees.

Lead design and implementation of a Databricks-driven data ecosystem, including lakehouse/EDW, IoT and streaming ingestion pipelines, ILM, global data governance, and dataset creation for advanced analytics.

Develop and optimize assortment strategies using statistical forecasting and data analysis. Analyze product, inventory, and financial metrics, partner with stakeholders, produce data-driven recommendations, monitor performance, and support demand planning initiatives.

Lead enterprise-scale Data & Analytics architecture and cloud modernization initiatives using AWS and Databricks. Assess legacy ecosystems, design target-state lakehouse and data warehouse solutions, define migration roadmaps, drive architecture governance, advise CXO stakeholders, and mentor delivery teams while ensuring security, scalability, and data governance.

Lead development and refactoring of optimization algorithms and end-to-end ML pipelines for supply chain, pricing, and inventory allocation. Build predictive models, use mathematical programming solvers, run experiments, monitor KPIs, and collaborate with stakeholders to drive replenishment and allocation improvements.

Design and implement high-performance APIs and microservices using Python and AWS, focusing on generative AI and scalable applications.

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.

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

The Senior Data Scientist will leverage advanced analytics, machine learning, and AI to develop analytics engines and collaborate with teams to enhance business value and communication of results.

Lead analytics consulting delivery, manage client relationships, drive account growth, and collaborate with teams to develop strategic analytics solutions for CPG and Retail clients.