Data Scientist

Job Description: echnical & Role Requirements Data Science / Engineering: Hands-on technical data analysis, data science, and prompt engineering skills Not junior-level; must contribute meaningfully in pods. Strong Python skills. Experience with: Google ADK framework Agent-to-Agent frameworks - Super agent & sub agents MCP (Agent-to-tools orchestration) Ability to orchestrate agents, manage autonomy, execution, and planning. About the Project. Agentic AI Use Cases: Client service management: onboarding, maintenance, offboarding automation. Example: Automating authorized representative changes (currently manual, many maker-checker steps). Goal: Build systems to augment and automate client servicing workflows. Credit portfolio management: Early warning systems, anomaly detection, proactive planning using ML and GenAI. Additional Skills Strong SQL for data analysis and transformation. Familiar with databases: Teradata, GCP, MongoDB (huge plus) Quantitative background preferred. Familiarity with: Evaluation frameworks (toxicity checks, coherent code, prompt evaluation). LLM-related tasks. Writing ADK FCPs, defining agents and tools. Must handle documentation: Monolith management, development documentation, monitoring controls and metrics, defining thresholds. Soft Skill Fit: Looking for individual passionate about AI. Must be self-starter , motivated, hungry, and proactive. Cannot be learning on the job—must demonstrate strong technical and practical experience.