Senior Data Scientist – GenAI

Responsibilities

• 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 Databricks and Azure AI services
• Build LLM-powered applications and orchestrate workflows using Lang Graph
• 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

• 8 - 10 years of professional work experience with at least 5 years in Data Science
• Proficiency in Python and SQL
• Practical exposure to Banking / Retail, supply chain domain problems such as logistics, distribution networks, or demand planning
• Experience with MLflow, NLP and model lifecycle management
• 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, Jump Start, Hugging Face
• 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.)
• Ability to work with IT and Data Engineering teams to help embed analytic outputs in business processes
• 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