Lead Data Scientist – GenAI

Job Description:

• 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

Requirements:

• 6+ years of experience working as a GenAI Data Science.
• 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.
• Unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.
• 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.