Jobs at Tiger Analytics

Own the vision, strategy, roadmap, requirements, KPIs, and go-to-market execution for insurance-focused data products. Collaborate with engineering and data science teams on products, proofs of concept, and demos; communicate progress to executives; and ensure compliance with BFS regulatory, risk, and compliance requirements.

Build and deploy production-grade GenAI and Agentic AI solutions for enterprise clients. Responsibilities include designing LLM applications, RAG systems, AI agents, and multi-agent workflows; integrating APIs, databases, and business applications; deploying and scaling cloud solutions; optimizing reliability, security, performance, and cost; and partnering with technical and business stakeholders from initial problem definition through production deployment.

Develop and refactor Python optimization algorithms using object-oriented programming for supply chain, inventory allocation, replenishment, and pricing optimization. Build predictive models, apply advanced statistical and optimization techniques to large datasets, and deliver data-driven solutions for retail and CPG clients. Collaborate with business stakeholders and data science teams, communicate analytical insights, coach colleagues, and apply current data science practices to business problems.

Leads Agile delivery across multiple teams or complex value streams, facilitating Scrum ceremonies, coaching teams, resolving impediments, managing dependencies and risks, and aligning stakeholders. The role oversees backlog and sprint goals, delivery metrics, release and change management, governance, reporting, and continuous improvement. Experience with analytics programs, cloud platforms, and tools such as Azure DevOps, Jira, Confluence, and Miro is valuable.

Leads AI and Generative AI engagements from discovery through production, serving as the client and technical delivery lead. Combines project management with hands-on architecture and development of LLM applications, RAG pipelines, AI agents, APIs, and cloud-based services. Coordinates cross-functional teams, manages risks and delivery milestones, translates business needs into technical solutions, and oversees evaluation, monitoring, deployment, and production readiness.

Manage analytics consulting projects from problem definition through solution delivery. Translate client business challenges into analytics designs, apply statistical and machine learning techniques, present insights to executives, and develop plans to operationalize solutions. Collaborate with global consulting, IT, and data engineering teams while managing stakeholders and project teams.

Designs and deploys enterprise knowledge graph solutions, semantic models, ontologies, taxonomies, and data governance frameworks. Establishes metadata management, lineage, business glossaries, stewardship workflows, and data quality standards. Collaborates with business, AI/ML, and engineering teams to translate domains into scalable architectures and integrate graphs with data fabrics, data meshes, and AI systems. Serves as a technical authority on client deployments and converts ambiguous requirements into production-ready data architecture blueprints.

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

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

Build high-performance API services and production-grade Generative AI systems. Design and implement end-to-end RAG pipelines, vector stores, embeddings, and latency-optimized generators. Develop agentic AI using LangChain/CrewAI/Semantic Kernel, integrate LLM APIs and AWS Bedrock, manage CI/CD and ML pipelines, and apply evaluation frameworks to detect hallucinations and optimize performance.

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

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.

Lead development and refactor optimization algorithms in Python for pricing and supply‑chain problems. Design and implement predictive models and mathematical optimization solutions, collaborate with cross‑functional teams, coach data scientists, and translate business requirements into data‑driven pricing and replenishment strategies.

Lead end-to-end delivery of enterprise Generative AI and Agentic AI programs, coordinating data science, machine learning, data engineering, product, architecture, and client teams. Oversee RAG pipelines, multi-agent ecosystems, knowledge graphs, production deployment, risks, dependencies, and technical challenges. Communicate program progress, blockers, and decisions to senior leadership and stakeholders while ensuring successful delivery of complex AI initiatives.

Designs and prototypes scalable agentic AI architectures across Azure, AWS, or GCP. Responsibilities include multi-agent orchestration, LLM applications, RAG pipelines, memory and vector search, enterprise integrations, cloud-native engineering, code reviews, AI governance, security guardrails, and stakeholder leadership. The role requires hands-on development, framework evaluation, and translating business needs into production-ready AI platforms.

Lead end-to-end executive and leadership recruiting across business and technology functions, including talent mapping, sourcing, stakeholder partnership, hiring strategy, offer negotiation, and closure. Mentor recruiters, monitor pipelines and hiring metrics, and develop talent strategies for data science, analytics, data engineering, and machine learning roles. The position partners with senior business leaders and supports recruiting growth in a global analytics consulting environment.

Leads enterprise HR analytics and AI consulting engagements from discovery through delivery. Translates business challenges into scalable analytics solutions, manages senior client stakeholders, and guides cross-functional data science, data engineering, and business analyst teams. Oversees HR data transformation initiatives, advises on workforce metrics, supports embedding analytics into business processes, and identifies opportunities for solution pitches and account expansion.

Lead analytics consulting engagements for enterprise clients by translating business challenges into AI and analytics solutions. Define agentic AI requirements, workflows, and outcomes; oversee end-to-end delivery; collaborate with technical and global teams; manage stakeholders and projects; apply statistical and machine learning techniques; and help operationalize solutions that deliver measurable business value.

Lead analytics consulting engagements by translating business objectives into analytical roadmaps, defining and governing KPIs, assessing data quality, and conducting hands-on data exploration with SQL and Python. Partner with stakeholders and Power BI developers to design metric structures, semantic models, wireframes, and dashboards that support strategic decision-making.

Manage, design, deploy, optimize, and scale persistent and transient AWS EMR clusters for batch data processing. Automate infrastructure with CloudFormation, Terraform, and CodePipeline; administer EC2, S3, and related AWS services; monitor pipelines; troubleshoot performance issues; and maintain security, patching, access controls, and cluster configurations. Preferred experience includes Hadoop, HDFS, AWS EKS, containerized workloads, and Kerberos.