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Assc Analytics & Model Analyst - Geo Modeler

Greater Noida, Uttar Pradesh

Live, first seen by us 18 days ago
Pay
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Work setting
Not stated
Employment
Not stated

Before you apply

New graduates
Entry level0–2 years of relevant experience in geospatial analytics, GeoAI, or a closely related field are preferredStrong foundation in machine learning, computer vision, and numerical methods, including experience with CNN-based architectures and modern vision models

What you’ll work on

Full posting
  • Develop scalable GeoAI pipelines for satellite and aerial imagery analysis

  • Build vision models for segmentation, object detection and change detection

  • Integrate Generative and Agentic AI into geospatial discovery and analysis workflows

  • Build and automate spatial processing pipelines in Python

  • Develop high-resolution datasets for land use, buildings, infrastructure and renewable assets

From the employer’s posting
Develop scalable GeoAI pipelines for large-scale satellite and aerial imagery analysis
Develop and apply vision models and large vision models for segmentation, object detection, building footprint extraction, renewable asset detection, image enhancement, and change detection
Integrate Generative AI and Agentic AI into geospatial data discovery, analysis, and production workflows
Build and automate spatial processing pipelines using Python and modern software development practices
Develop and analyze high-resolution datasets including land use and land cover, buildings, infrastructure, and renewable energy assets
Education & alternatives
Education - Post-graduate degree (Masters or PhD) in Geoinformatics, Remote Sensing, Earth Sciences, Computer Science, Data Science, Artificial Intelligence or Machine Learning from a reputable institution Responsibilities
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Posting record

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Status in our records
Live
First seen by us
Oct 26, 202618 days ago
Recorded sightings
35
Last seen by us
Nov 13, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 18

Similar jobs usually come down between day 5 and day 43.

At Moody's, jobs usually come down by about day 15.

From 14,545 similar postings that came down, and 78 of Moody's’s. Coming down is not always a hire.

Moody's is hiring

54 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Takes jobs down at a usual pace
  • 11% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • Keras
  • Matplotlib
  • NumPy
  • pandas
  • Plotly
  • PyTorch
  • scikit-learn
  • SciPy
  • TensorFlow
Where the posting names them
- Solid understanding of remote sensing techniques, including image classification and segmentation, change detection and decorrelation, and processing of hyperspectral and multispectral imagery - Proficiency in Python with hands-on experience across machine learning frameworks (Scikit-Learn, TensorFlow, Keras, PyTorch, GluonCV), computer vision and geospatial libraries (OpenCV, GDAL, GeoPandas, Rasterio, Rasterstats, Shapely, Fiona, NumPy, Pillow), data processing and analytics tools (Pandas, NumPy, SciPy),and visualization libraries (Matplotlib, Seaborn, Plotly) - Familiarity with GIS tools including the ESRI suite, QGIS, and GRASS; exposure to Google Earth Engine is a plus
- Integrate Generative AI and Agentic AI into geospatial data discovery, analysis, and production workflows - Build and automate spatial processing pipelines using Python and modern software development practices - Develop and analyze high-resolution datasets including land use and land cover, buildings, infrastructure, and renewable energy assets

Your next step

Complete your application on careers.moodys.com. The employer’s form will show what is required.

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About Moody's

People
About 5,300 in 2025, up 10% from the year before.Annual report (SEC Form 10-K)
Company
Listed as MCO.

Demand for Analyst roles

New Analyst postings at the employers we follow are up 23% over the last 6 weeks compared with the 6 before.

Weekly new Analyst postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 993, the most 1,515, and the latest week had 1,515.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Analyst, by the work the posting describes.

Analysts answer business questions with data. They pull numbers with SQL, build reports and dashboards, and explain what changed and why to the people making decisions.

Most postings ask for SQL, spreadsheets, a dashboard tool such as Tableau or Power BI, and clear writing.

Unlike a data scientist, an analyst mostly explains what happened rather than building models that predict what will.

Job description

View original posting ↗

At Moody's, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they are—with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. Moody’s is transforming how the world sees risk. As a global leader in ratings and integrated risk assessment, we’re advancing AI to move from insight to action—enabling intelligence that not only understands complexity but responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence.

If you are excited about this opportunity but do not meet every single requirement, please apply! You still may be a great fit for this role or other open roles. We are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity. 


Skills and Competencies

  • 0–2 years of relevant experience in geospatial analytics, GeoAI, or a closely related field are preferredStrong foundation in machine learning, computer vision, and numerical methods, including experience with CNN-based architectures and modern vision models
  • Solid understanding of remote sensing techniques, including image classification and segmentation, change detection and decorrelation, and processing of hyperspectral and multispectral imagery
  • Proficiency in Python with hands-on experience across machine learning frameworks (Scikit-Learn, TensorFlow, Keras, PyTorch, GluonCV), computer vision and geospatial libraries (OpenCV, GDAL, GeoPandas, Rasterio, Rasterstats, Shapely, Fiona, NumPy, Pillow), data processing and analytics tools (Pandas, NumPy, SciPy),and visualization libraries (Matplotlib, Seaborn, Plotly)
  • Familiarity with GIS tools including the ESRI suite, QGIS, and GRASS; exposure to Google Earth Engine is a plus
  • Demonstrated proficiency in artificial intelligence concepts, with hands-on experience using AI tools to streamline workflows and enhance operational efficiency. Proven ability to implement AI-powered solutions to solve business challenges. Demonstrates a growing awareness of AI risk management and a commitment to responsible and ethical AI use

Education

  • Post-graduate degree (Masters or PhD) in Geoinformatics, Remote Sensing, Earth Sciences, Computer Science, Data Science, Artificial Intelligence or Machine Learning from a reputable institution

Responsibilities

  • Develop scalable GeoAI pipelines for large-scale satellite and aerial imagery analysis using AI and ML, computer vision, and remote sensing techniques
  • Develop and deploy scalable GeoAI pipelines and vision models that power large-scale geospatial analytics, exposure intelligence, and catastrophe risk solutions
  • Develop and apply vision models and large vision models for segmentation, object detection, building footprint extraction, renewable asset detection, image enhancement, and change detection
  • Integrate Generative AI and Agentic AI into geospatial data discovery, analysis, and production workflows
  • Build and automate spatial processing pipelines using Python and modern software development practices
  • Develop and analyze high-resolution datasets including land use and land cover, buildings, infrastructure, and renewable energy assets
  • Support model evaluation, visualization, metadata management, documentation, and productionization of GeoAI solutions

About the Team
Our Geospatial Team within the Model Development Group is responsible for developing critical geospatial datasets, exposure intelligence, and modeling components that underpin Moody's industry-leading catastrophe risk solutions used by more than 400 clients worldwide. By joining our team, you will be part of exciting work in developing geospatial datasets for catastrophe models, advancing AI-powered geospatial analytics, and delivering innovative solutions in renewable energy intelligence, event response, and damage assessment to support global risk insights and decision-making.


Moody’s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender expression, gender identity or any other characteristic protected by law.

Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody’s Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.

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Location & working pattern

Greater Noida, Uttar Pradesh

- 0–2 years of relevant experience in geospatial analytics, GeoAI, or a closely related field are preferredStrong foundation in machine learning, computer vision, and numerical methods, including experience with CNN-based architectures and modern vision models - Solid understanding of remote sensing techniques, including image classification and segmentation, change detection and decorrelation, and processing of hyperspectral and multispectral imagery - Proficiency in Python with hands-on experience across machine learning frameworks (Scikit-Learn, TensorFlow, Keras, PyTorch, GluonCV), computer vision and geospatial libraries (OpenCV, GDAL, GeoPandas, Rasterio, Rasterstats, Shapely, Fiona, NumPy, Pillow), data processing and analytics tools (Pandas, NumPy, SciPy),and visualization libraries (Matplotlib, Seaborn, Plotly)
More source context
Education - Post-graduate degree (Masters or PhD) in Geoinformatics, Remote Sensing, Earth Sciences, Computer Science, Data Science, Artificial Intelligence or Machine Learning from a reputable institution Responsibilities - Develop scalable GeoAI pipelines for large-scale satellite and aerial imagery analysis using AI and ML, computer vision, and remote sensing techniques - Develop and deploy scalable GeoAI pipelines and vision models that power large-scale geospatial analytics, exposure intelligence, and catastrophe risk solutions
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