• Own and extend our offline eval suite across products — datasets (capability + regression), judges, metrics • Build and maintain online quality dashboards: resolution rate, CSAT, thumbs up/down, LLM-as-judge signals, error rate, latency • Close the production feedback loop: mine failure patterns from real traffic → turn them into regression cases → propose fixes to Product and domain experts • Harden methodology: judge stability, non-determinism handling • Translate numbers into decisions – weekly syncs, clear trade-offs, no dashboards for their own sake

• Own and extend our offline eval suite across products — datasets (capability + regression), judges, metrics • Build and maintain online quality dashboards: resolution rate, CSAT, thumbs up/down, LLM-as-judge signals, error rate, latency • Close the production feedback loop: mine failure patterns from real traffic → turn them into regression cases → propose fixes to Product and domain experts • Harden methodology: judge stability, non-determinism handling • Translate numbers into decisions – weekly syncs, clear trade-offs, no dashboards for their own sake

• Own and extend our offline eval suite across products — datasets (capability + regression), judges, metrics • Build and maintain online quality dashboards: resolution rate, CSAT, thumbs up/down, LLM-as-judge signals, error rate, latency • Close the production feedback loop by mining failure patterns from real traffic and proposing fixes • Harden methodology: judge stability and non-determinism handling • Translate numbers into decisions in weekly syncs with clear trade-offs

Role Description Tiger Analytics is looking for experienced Data Scientists GenAI to join our fast-growing advanced analytics consulting firm. We are seeking a highly skilled and experienced Lead Data Scientist with strong expertise in GenAI modelling. The ideal candidate will have a proven track record of designing, developing, and deploying scalable GenAI solutions, while leading projects and mentoring teams. This role requires deep technical expertise, hands-on coding experience, and the ability to collaborate closely with clients and stakeholders to translate business needs into robust analytical solutions. - Work on the latest applications of data science to solve business problems - Work directly with client stakeholders to translate business problems into high level analytics solution designs - Present analytic solutions to business audiences highlighting robustness of the solution and how it could help generate business value - Develop end-to-end solutions based on in-depth understanding of business problems to ensure analytics solutions are delivered efficiently, predictably, and sustainably - Design and develop machine learning and Generative AI solutions using RAG - Build LLM-powered applications leveraging Azure OpenAI and orchestrate workflows using LangGraph - Develop agentic AI workflows for automation, insights generation, and decision support - Implement Document Intelligence solutions for extracting insights from unstructured data - Participate in discussions with team members to select and apply relevant analytic techniques and create actionable business insights - Responsible for making presentations to senior management, communicating results to business teams, and develop plans to help operationalize analytic solution Qualifications - 7+ years of experience working as a GenAI Data Scientist - Proficiency in Python and SQL - Experience with MLflow and model lifecycle management - Experience with Python from a functional programming paradigm, able to manage dependencies and virtual environments, along with version control in git - Generative AI Knowledge: Solid understanding of latest-generation AI concepts including LLMs, prompt engineering, retrieval-augmented generation (RAG), and other contemporary generative AI applications - Experience with sequential algorithms (e.g., LSTM, RNN, transformer, etc.) - Experience with Bedrock, JumpStart, HuggingFace - Experience evaluating ethical implications of AI and controlling for them (e.g., red-teaming) - Expertise in supervised learning and unsupervised learning along with experience in deep learning and transfer learning - Experience in generative algorithms (e.g., GAN, VAE, etc.) as well as pre-trained models (e.g., LLaMa, SAM, etc.) - Experience developing models from inception to deployment - 5-10 years of professional work experience with at least 5 years in Data Science - Experience building end-to-end ML pipelines in production - Familiarity with CI/CD pipelines, monitoring, and model governance - Ability to design scalable and reliable AI systems - Bachelor's in Business Analytics or equivalent work experience Benefits - Significant career development opportunities exist as the company grows - The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility Company Description Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.