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 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
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, 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.)
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