Data Scientist

• 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.

Do you have experience in Software documentation?, + 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., + 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.