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The Role
Design, test, and evaluate LLM-based underwriting agents for credit-risk use cases. Translate underwriting judgment into auditable AI workflows, define evaluation frameworks, analyze bureau/tradeline and borrower-risk signals, compare AI outputs to historical decisions and outcomes, and collaborate with engineers, credit experts, and stakeholders to build governed, human-in-the-loop underwriting solutions.
Summary Generated by Built In
StratLytics is hiring an AI Scientist — Credit Risk & Agentic AI for our Bhubaneswar office to work on a high-impact AI underwriting initiative for a North American fintech client.
This role is ideal for someone who combines credit-risk analytics, applied machine learning, LLM reasoning, evaluation design, and business judgment. This is not a generic prompt-engineering role. The selected candidate will help design, test, evaluate, and improve AI agents that analyze credit and underwriting data in a controlled, evidence-cited, human-in-the-loop environment.
Key responsibilities include:
- Design AI reasoning frameworks for credit-risk and underwriting use cases.
- Translate underwriting judgment into structured, testable, and auditable AI workflows.
- Work on bureau/tradeline analysis, borrower-risk signals, shadow debt patterns, data-integrity flags, and score reconciliation.
- Design prompts, reasoning flows, evaluation criteria, and structured outputs for LLM-based underwriting agents.
- Define evaluation frameworks for underwriter alignment, incremental signal, hallucination risk, data-integrity detection, and decision quality.
- Compare AI outputs against historical underwriter decisions, credit scores, model outputs, and repayment/loss outcomes.
- Partner with AI engineers, data engineers, credit-risk experts, and platform teams to build governed AI underwriting solutions.
- Participate in internal and client-facing discussions with senior stakeholders.
Requirements
Required:
- 5+ years of experience in data science, credit-risk analytics, underwriting analytics, risk modeling, or applied machine learning.
- Strong understanding of credit-risk concepts such as bureau data, credit scores, scorecards, delinquency, utilization, inquiries, tradelines, repayment behavior, loss/default outcomes, and underwriting policy.
- Strong Python and SQL skills.
- Experience with statistical modeling, machine learning, model validation, or analytical backtesting.
- Familiarity with LLMs, prompt design, structured outputs, RAG, or agentic AI systems.
- Ability to define evaluation frameworks and interpret model/AI outputs critically.
- Strong communication skills and ability to work with business, credit, data science, and engineering teams.
- Willingness to work from the StratLytics Bhubaneswar office.
Preferred:
- Experience in fintech, lending, NBFC, banking, credit bureau, SME lending, consumer lending, merchant cash advance, or commercial underwriting.
- Experience with consumer bureau or commercial bureau data.
- Exposure to Claude, OpenAI, AWS Bedrock, LangChain, LangGraph, LlamaIndex, or similar tools.
- Familiarity with Pydantic, JSON schemas, evaluation harnesses, model governance, explainability, or human-in-the-loop AI workflows.
- Prior consulting or client-facing experience.
Benefits
- Competitive compensation aligned with market standards, based on experience and capability.
- Opportunity to work on cutting-edge AI applications in real financial-services decisioning.
- Exposure to a high-impact North American fintech AI underwriting programme.
- Work on practical, governed AI systems rather than generic chatbot demos.
- Collaborate with experienced data science, risk, AI, and engineering professionals.
- Opportunity to build expertise in agentic AI, LLM evaluation, credit-risk analytics, and human-in-the-loop decisioning.
- Candidates from other cities are welcome to apply if they are open to relocating to Bhubaneswar.
Skills Required
- 5+ years in data science, credit-risk analytics, underwriting analytics, risk modeling, or applied machine learning.
- Strong understanding of credit-risk concepts (bureau data, credit scores, scorecards, delinquency, utilization, inquiries, tradelines, repayment behavior, loss/default outcomes, underwriting policy).
- Strong Python skills.
- Strong SQL skills.
- Experience with statistical modeling, machine learning, model validation, or analytical backtesting.
- Familiarity with LLMs, prompt design, structured outputs, RAG, or agentic AI systems.
- Ability to define evaluation frameworks and interpret model/AI outputs critically.
- Strong communication skills and ability to work with business, credit, data science, and engineering teams.
- Willingness to work from the StratLytics Bhubaneswar office (relocation if applicable).
- Experience in fintech, lending, NBFC, banking, credit bureau, SME lending, consumer lending, merchant cash advance, or commercial underwriting.
- Experience with consumer bureau or commercial bureau data.
- Exposure to Claude, OpenAI, AWS Bedrock, LangChain, LangGraph, or LlamaIndex.
- Familiarity with Pydantic, JSON schemas, evaluation harnesses, model governance, explainability, or human-in-the-loop AI workflows.
- Prior consulting or client-facing experience.
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The Company
What We Do
StratLytics is a data science and management consulting firm that develops AI-powered decision intelligence platforms and provides advanced analytics, machine learning, and data engineering solutions. It specializes in transforming complex data and workflows into governed business decisions for sectors including financial services, energy, utilities, retail, and industrial supply chains, focusing on improving decision-making and driving growth.
