Tiger Analytics

Data Engineer

• Responsible for designing, building, and maintaining data pipelines, data integration processes, and data infrastructure.
• Collaborate closely with data scientists, analysts, and other stakeholders to ensure efficient data flow and support data-driven decision making across the organization.

GenAI Data Engineer

Data Scientist

• Responsible for refactoring the Optimization algorithm written in Python using Object Oriented Programming
• Work on the latest applications of data science to solve business problems in the Supply chain and optimization space of Retail and/or CPG.
• Utilize advanced statistical techniques and data science algorithms to analyze large datasets and derive actionable insights related to replenishment optimization and inventory allocation.
• Develop and implement predictive models and optimization algorithms to improve inventory management, reduce stockouts, and optimize resource allocation across the supply chain.
• Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions.
• Design and execute experiments to evaluate the effectiveness of different replenishment strategies and allocation policies.
• Monitor and analyze key performance indicators (KPIs) related to replenishment and supply chain allocation, and provide recommendations for continuous improvement.
• Stay abreast of industry trends and best practices in data science, replenishment optimization, and supply chain management, and leverage this knowledge to drive innovation within the organization.
• Collaborate, coach, and learn with a growing team of experienced Data Scientists.

Senior Data Scientist – Operations Research

• Lead statistical analysis and modeling efforts for program evaluation and business impact assessment
• Design and execute evaluation methodologies (e.g., A/B testing, quasi-experimental designs, causal inference)
• Apply advanced statistical techniques such as regression, hypothesis testing, time-series analysis, and multivariate analysis
• Develop predictive and explanatory models to assess program outcomes and performance
• Translate complex analytical findings into clear, actionable insights for business and leadership stakeholders
• Work closely with cross-functional teams (product, business, strategy) to define evaluation metrics and success criteria
• Ensure data quality, statistical validity, and reproducibility of analyses
• Mentor junior team members and review analytical work for rigor and accuracy
• Collaborate, coach, and learn with a growing team of experienced Data Scientists.

Senior Data Scientist – Statistical Analysis

AI Engineer

• Lead the architecture, design, and implementation of GenAI/Agentic AI based solutions into real-world enterprise-ready applications.
• Collaborate with AI/ML teams to operationalize models using APIs, embeddings, vector databases, and prompt engineering techniques.
• Own full-stack development and integration of GenAI features into web/mobile applications.
• Establish best practices for scalable, secure, and maintainable AI-powered application development.
• Optimize application performance, latency, and reliability of AI features in production.
• Drive DevOps practices for continuous delivery and monitoring of AI-enabled services in production.
• Mentor engineers and guide code reviews, architectural decisions, and DevOps practices.
• Guide engineering teams in code quality, architectural reviews, and technical mentoring.
• Evaluate emerging GenAI tools and LLM frameworks (OpenAI, LangChain etc.) and make build-vs-buy recommendations.
• Oversee application-level development, testing, and deployment.

Generative AI Leader – Architect

Architect

• Responsible for Architecture, Designing and implementing best data practices on the Azure platform.

Senior Architect – Azure Databricks

Technical Project Manager

• Own and maintain integrated technical and business roadmaps across 4+ concurrent GenAI tracks (Contract Digitisation, Contract Q&A, Finance Chat Agent, Supply Chain/Pricing Agentic Workflows)
• Translate business priorities into actionable product requirements and development sprints
• Balance short-term delivery milestones with long-term strategic AI capabilities
• Identify dependencies and synergies across tracks to maximise reusability and accelerate delivery
• Serve as primary liaison between client business stakeholders and Tiger Analytics delivery teams
• Conduct regular prioritisation sessions with business leaders to align roadmap with evolving needs
• Manage expectations through transparent communication of timelines, risks, and tradeoffs
• Present progress updates and strategic recommendations to senior leadership, including the Head of Decision Intelligence
• Collaborate with FDEs embedded in each track to ensure technical feasibility and quality
• Facilitate cross-track knowledge sharing and best practice adoption
• Work with engineering teams on architecture decisions involving Databricks, PowerBI semantic models, and agentic frameworks
• Ensure GenAI solutions meet enterprise standards for security, scalability, and governance**

Technical Project Manager – Gen AI

Full-stack Engineer

• Collaborate with business teams to design, develop, and deploy AI agents that drive efficiency and innovation.
• Provide guidance and technical oversight to users and teams building agents, ensuring alignment with enterprise standards.
• Develop, test, and maintain AI agents using tools such as Gemini Enterprise, Agentforce, Sierra.AI, DevRev, and other emerging platforms.
• Monitor production agents; troubleshoot and resolve performance or functionality issues as they arise.
• Conduct comprehensive security and functionality testing prior to production release.
• Develop and enforce policies, guidelines, and guardrails for AI and agent testing.
• Serve as a subject matter expert (SME) for AI strategy, brainstorming, and implementation ideas across business functions.
• Stay current on emerging AI technologies and recommend best practices for enterprise adoption.

Lead Engineer – Agentic AI

• Design and lead the development of large-scale, cloud-native Generative AI platforms and solutions.
• Architect and design cloud-native, scalable GenAI platforms leveraging Microsoft Azure services.
• Define end-to-end system architectures integrating GenAI components with enterprise applications.
• Design and govern API-first architectures, including REST/GraphQL APIs, service contracts, and integration patterns.
• Implement security-by-design principles, including identity and access management, network security, data protection, and compliance standards.
• Design and optimize event-driven architectures using messaging, streaming, and asynchronous processing patterns.
• Lead architectural decisions around scalability, performance, reliability, and cost optimization.
• Collaborate closely with engineering, data, AI, and platform teams to ensure successful implementation of architectural designs.
• Provide technical leadership, mentorship, and architectural guidance across teams.
• Establish best practices, standards, and reference architectures for GenAI solutions.
• Review and approve solution designs to ensure alignment with enterprise and cloud architecture standards.

GenAI Architect

• Tiger Analytics is a global leader in AI and advanced analytics consulting, empowering Fortune 1000 companies to solve their toughest business challenges. We are on a mission to push the boundaries of what AI can do, providing data-driven certainty for a better tomorrow. Our diverse team of over 6,000 technologists and consultants operates across five continents, building cutting-edge ML and data solutions at scale. Join us to do great work and shape the future of enterprise AI.
• We are looking for a highly skilled **GenAI Engineer** with strong hands-on experience in building, evaluating, and deploying advanced Generative AI systems. The ideal candidate will have deep expertise in agentic frameworks, model fine-tuning, and reinforcement learning, along with a strong focus on experimentation, reliability, and hallucination mitigation beyond prompt engineering.

GenAI Engineer

Consultant

• Engage with client teams to gather, analyze, and document business and analytical requirements
• Translate client requirements into clear specifications for offshore delivery teams
• Act as the primary onshore point of contact for project coordination and execution
• Manage projects, conduct client presentations, and provide regular status updates
• Write basic SQL queries to extract data and perform data analysis to support business insights
• Convert client's requests into well-defined project requirements and solution approaches
• Collaborate effectively with offshore teams to ensure timely and accurate delivery
• Understand Tiger’s capabilities and proactively discuss relevant solutions with clients

Consultant, Senior Consultant – Lifesciences

Manager

• Lead analysis and solution design for Market Access and Speciality Pharmacy use cases
• Work hands-on with SQL for Analytical Requirement Document (ARD) design and development
• Apply data modelling and data warehousing concepts to support scalable analytics solutions
• Own Tableau report development, including KPI definition, dashboard design, and wireframing
• Translate complex business requirements into clear, data-driven analytical solutions
• Engage directly with clients, clearly articulating insights and recommendations
• Manage, mentor, and guide an offshore delivery team, ensuring timely and high-quality execution

Manager – Market Access, Pharma & Life Sciences

Client Partner

• - As a client partner, you will have overall responsibility for delivery, account management, client relationships, and account growth.
• - You will be responsible for demonstrating business value through solutions that help meet strategic, operational, and tactical objectives, and making executive presentations.
• - You will be responsible for scaling the pilots / POCs to a long-term transformative program and delivering continuous business value.
• - You will work with the client’s business stakeholders to understand key business questions, challenges, and information needs, and help develop an analytics roadmap that identifies and prioritizes key analytics use cases for execution.
• - You will be collaborating with sales leaders (both new sales and account sales) to create the right POVs and proposals to help win new logos and drive growth in existing clients.
• - You will work on some of the latest data science applications to solve complex business problems in Consumer Product Goods (CPG) and Retail.
• - You will lead a team of data and analytics professionals and directly work with key client stakeholders to help define the business problem and determine solution requirements.

Associate Director – Client Partner, Banking

Machine Learning Engineer

• Design, build, and optimize high-performance **APIs and microservices** using **Python (Fast API)** deployed on **AWS Fargate (ECS)**.
• Integrate **LLM and Generative AI APIs** using providers such as **AWS Bedrock**, **OpenAI**, and others.
• Collaborate with ML and DevOps teams to design **CI/CD and MLOps pipelines** within the **AWS ecosystem**.
• Contribute to architectural decisions around scalability, latency management, and backend efficiency for AI-powered systems.
• (Preferred) Leverage familiarity with **Bedrock Agent Core** services to integrate intelligent agent capabilities.
• Develop and maintain **JSON RESTful APIs**, adhering to **OpenAI API** conventions and best practices.

• Tiger Analytics is looking for experienced Senior Data Scientists to join our fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.
• As a Data Scientist, you will apply strong expertise through the use of machine learning, data mining, and information retrieval to design, prototype, and build next generation advanced analytics engines and services. You will collaborate with cross-functional teams and business partners to define the technical problem statement and hypotheses to test. You will develop efficient and accurate analytical models which mimic business decisions and incorporate those models into analytical data products and tools. You will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results.
• **Key Responsibilities**
• - Collaborate with business partners to develop innovative solutions to meet objectives utilizing cutting edge techniques and tools.
• - Develop, test, and deploy data science solutions using Python, SQL, and PySpark on enterprise platforms such as Databricks.
• - Collaborate with data scientists to translate models into production-ready code.
• - Implement CI/CD pipelines and manage code repositories using GitHub Enterprise.
• - Design and optimize mathematical programming and machine learning models for real-world applications.
• - Work independently to break down complex problems into actionable development tasks.
• - Ensure code quality, scalability, and maintainability in a production environment.
• - Contribute to sprint planning, documentation, and cross-functional collaboration.
• - Collaborate, coach, and learn with a growing team of experienced Data Scientists.
• - Stay connected with external sources of ideas through conferences and community engagements

Senior Data Scientist – Semiconductor

• Tiger Analytics is looking for experienced Data Scientists to join our fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.
• As a Data Scientist, you will apply strong expertise in AI through the use of machine learning, data mining, and information retrieval to design, prototype, and build next generation advanced analytics engines and services. You will collaborate with cross-functional teams and business partners to define the technical problem statement and hypotheses to test. You will develop efficient and accurate analytical models which mimic business decisions and incorporate those models into analytical data products and tools. You will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results.
• **Key Responsibilities**
• - Implement efficient Retrieval-Augmented Generation (RAG) architectures and integrate with enterprise data infrastructure.
• - Collaborate with cross-functional teams to integrate solutions into operational processes and systems supporting various functions.
• - Stay up to date with industry advancements in AI and apply modern technologies and methodologies to our systems.
• - Design, build and maintain scalable and robust real-time data streaming pipelines using technologies such as gcp, vertex ai, s3, AWS bedrock, Spark streaming, or similar.
• - Develop data domains and data products for various consumption archetypes including Reporting, Data Science, AI/ML, Analytics etc.
• - Ensure the reliability, availability, and scalability of data pipelines and systems through effective monitoring, alerting, and incident management.
• - Implement best practices in reliability engineering, including redundancy, fault tolerance, and disaster recovery strategies.
• - Collaborate closely with DevOps and infrastructure teams to ensure seamless deployment, operation, and maintenance of data systems.
• - Mentor junior team members and engage in communities of practice to deliver high-quality data and AI solutions while promoting best practices, standards, and adoption of reusable patterns.
• - Apply AI solutions to insurance-specific data use cases and challenges.
• - Partner with architects and stakeholders to influence and implement the vision of the AI and data pipelines while safeguarding the integrity and scalability of the environment.