Moody’s Hiring: Associate Analytics & Model Analyst 2026:-
Moody’s is inviting applications for the position of Associate Analytics & Model Analyst (14415) in Noida, Greater Noida Expressway. This opportunity is suitable for freshers and early-career candidates with 0–2 years of academic, internship, or professional experience in data analytics, statistical analysis, research, or related analytical fields.
| Company: | Moody’s |
| Job Role: | Associate Analytics & Model Analyst |
| Job Category: | Data Analytics / Model Development |
| Experience: | 0–2 Years |
| Salary: | As per company Standards |
| Application Deadline: | ASAP |
Role Overview:-
The Associate Analytics & Model Analyst will analyse different types of datasets to identify patterns, trends, anomalies, and opportunities for improvement.
The role involves using SQL for data extraction and validation, Python libraries such as Pandas and NumPy for data processing, and statistical techniques to support analytical studies and business decisions.
The selected candidate will also contribute to property insurance datasets, spatial data layers, catastrophe modelling research, data quality initiatives, process automation, and agentic AI-driven solutions.
Candidates should have strong analytical thinking, SQL proficiency, working knowledge of Python, and an interest in using AI tools to improve analytical workflows.
Educational Requirements:-
Candidates must have a Bachelor’s or Master’s degree in one of the following fields:
- Engineering – B.E. / B.Tech.
- M.E. / M.Tech.
- Data Science.
- Statistics.
- Mathematics.
- Computer Science.
- Applied Statistics.
- Geographic Information Systems (GIS).
- Remote Sensing.
- Actuarial Science.
- Other quantitative or analytical disciplines.
Additional Qualification:
- MBA or PGDM with a specialisation in Data Analytics is also considered.
Key Skills Required:-
1. SQL and Database Skills
- Strong SQL proficiency.
- Data extraction and retrieval.
- Data validation.
- Data reconciliation.
- Data quality assurance.
- Analytical problem-solving using SQL.
- Identifying inconsistencies in datasets.
- Working with large datasets.
2. Python and Data Analytics Skills
- Working knowledge of Python.
- Pandas library.
- NumPy library.
- Data processing and manipulation.
- Data analysis and interpretation.
- Exploratory data analysis.
- Structured and semi-structured data handling.
- Analytical problem-solving.
3. Statistical and Analytical Skills
- Statistical analysis.
- Logical reasoning.
- Critical thinking.
- Exploratory research.
- Trend and pattern identification.
- Anomaly detection.
- Data quality assessment.
- Root cause analysis.
- Analytical reporting.
- Risk-related analysis.
4. AI and Automation Skills
- Strong prompting skills.
- Agentic AI concepts and capabilities.
- Interest in AI-driven analytical solutions.
- AI-assisted workflow improvement.
- Process automation.
- Improving operational efficiency through AI tools.
- Ability to learn emerging analytical technologies.
5. Geospatial and Domain Skills
- Geospatial data analysis.
- Spatial data layers.
- Property exposure analytics.
- Property insurance datasets.
- Catastrophe risk modelling fundamentals.
- Property intelligence.
- Risk-related data analysis.
Geospatial and catastrophe risk knowledge are important areas of domain development for this role; the supplied description does not list a specific GIS software package as mandatory.
6. Soft Skills
- Strong communication skills.
- Presentation skills.
- Attention to detail.
- Independent working ability.
- Teamwork and collaboration.
- Adaptability.
- Quick learning ability.
- Critical thinking.
- Problem-solving.
- Ability to communicate findings to technical and non-technical stakeholders.
Roles and Responsibilities:-
1. Data Analysis and Exploratory Research
- Analyse structured, semi-structured, and geospatial datasets.
- Identify patterns, trends, anomalies, and opportunities for improvement.
- Perform exploratory research and analytical studies.
- Apply statistical and analytical techniques to support business insights.
- Support decision-making through data-driven findings.
- Contribute to risk-related analytical studies.
2. Property Data and Analytical Solutions
- Support the development of property insurance datasets.
- Contribute to the enhancement of spatial data layers.
- Assist in developing analytical products and data-driven solutions.
- Improve the accuracy and usability of property-related information.
- Support property exposure assessment and catastrophe risk modelling initiatives.
3. Data Validation and Quality Assurance
- Perform data validation and reconciliation activities.
- Conduct testing and quality assurance of datasets.
- Improve data accuracy, completeness, and consistency.
- Identify data quality issues and inconsistencies.
- Investigate data-related problems and document findings.
- Identify root causes and contribute to timely resolution efforts.
4. Statistical Analysis and Risk Research
- Apply statistical methods to analyse datasets.
- Support analytical studies related to catastrophe modelling.
- Conduct research to improve property data and analytical products.
- Assist with risk-related analysis and business insights.
- Support product development and data improvement initiatives.
5. Reporting and Documentation
- Prepare analytical reports and summaries.
- Develop dashboards and presentations.
- Document analytical findings and data issues.
- Communicate insights and recommendations clearly.
- Present findings to technical and non-technical stakeholders.
- Maintain clear documentation for analytical activities.
6. Cross-Functional Collaboration
- Work with analysts, modelers, data scientists, and engineers.
- Collaborate with global stakeholders across different teams.
- Coordinate with teams across India, London, and the United States.
- Contribute to multidisciplinary analytical projects.
- Share findings and support collaborative problem-solving.
7. Process Automation and Agentic AI
- Contribute to process optimisation initiatives.
- Support automation activities within analytical workflows.
- Explore agentic AI-driven solutions.
- Use AI capabilities to improve process efficiency.
- Identify opportunities to streamline repetitive analytical tasks.
- Support the adoption of innovative analytical tools and approaches.
8. Domain Knowledge Development
- Develop expertise in catastrophe risk.
- Build knowledge of property exposure analytics.
- Understand geospatial data and spatial analysis.
- Learn related analytical tools and methodologies.
- Develop an understanding of property insurance data and risk-focused products.
About Moody’s:-
Moody’s is a global provider of financial intelligence, data, analytics, and risk assessment solutions. The company helps organisations understand risks, evaluate opportunities, and make informed decisions through its research, technology, and analytical capabilities.
Its work spans areas such as credit risk, financial markets, data analytics, and risk management.
Moody’s Hiring: Associate Analytics & Model Analyst 2026 Application Process:-
Apply Link:- Click Here To Apply
Note:- Only the shortlisted candidates will be notified for the further interview process.
