Strategic Intelligence Data Scientist: AI-Driven Risk

Moody's Corporation; United States; On-site; USD 117,000 - 169,000; Full time

Benefits offered by this job

Medical, dental, vision

401(k) plan with company match

Paid time off

Parental leave

Tuition reimbursement

Job summary

Moody’s Corporation is seeking a Data Scientist to build AI-enabled predictive models and analytics across commercial, customer, product, and portfolio use cases. You will ingest qualitative and unstructured information using NLP/LLMs, convert content into structured signals, and enrich views by combining internal and external data sources.

The role emphasizes propensities, churn, cross-sell opportunities, and risk assessment with dashboards delivered via Power BI/Tableau.

Qualifications

• 5+ years in data science, ML, or quantitative modelling
• Strong Python and SQL skills; NLP and DL libraries
• Experience with NLP, embeddings, prompts, and evaluation

Responsibilities

• Build AI-enabled predictive models and analytics
• Ingest unstructured data using NLP and LLMs
• Combine internal and external data sources for analytics
• Develop and maintain propensity-to-buy models
• Create account health and churn prediction models
• Quantify customer/portfolio risk with ML techniques
• Apply ML/AI to improve forecasting and segmentation
• Operationalize models in Databricks and Azure with governance

Skills

Python (pandas, scikit-learn)

SQL

NLP & LLM

Predictive modeling

Statistics & econometrics

Databricks / Spark

Model deployment & governance

BI visualization (Power BI/Tableau)

Communication to non-technical

Unstructured data handling

Education

Bachelor’s degree in Economics, Statistics, Math, Data Science, CS, Engineering

Master’s degree or PhD preferred

Equivalent practical experience

Certifications in Databricks/cloud ML (preferred)

Tools

Databricks

Azure

Spark

MLflow

Job description

Moody’s Corporation is seeking a Data Scientist to build AI-enabled predictive models and analytics across commercial, customer, product, and portfolio use cases. You will ingest qualitative and unstructured information using NLP/LLMs, convert content into structured signals, and enrich views by combining internal and external data sources.

The role emphasizes propensities, churn, cross-sell opportunities, and risk assessment with dashboards delivered via Power BI/Tableau.