Sr. Modeling Analyst
About RMS
There’s a 1% chance an earthquake will cause $50 billion of insured loss within the next 12 months and a 5% chance that a hurricane will cause $60 billion of insured losses next year. At RMS, we turn risks into real numbers. How? By building simulation models that allow insurers and investors to understand and manage their global risks--from hurricanes, quakes, and wildfires, to cyberattacks, terror attacks, and pandemics. Why? We want to build a more resilient world, and we’re on a mission to help make every risk known.
Insurers, reinsurers, investors, financial institutions, governments, and NGOs trust RMS solutions to better understand and manage catastrophe risks. RMS was founded in 1989 by Stanford scientists who created our first model for California Earthquake. Today, RMS has some 1,300 employees across 13 offices in the US, London, Bermuda, Zurich, India, China, Japan, Singapore, and Australia, and over 1000 products and models now covering six continents.
RMS helped pioneer the natural catastrophe model market we now lead – and we continue to innovate. In May 2019, we announced RMS Risk Intelligence™ (RI), an open-standard platform for strategic risk management. Through this purpose-built platform, clients can tap into RMS HD models, rich data layers, intuitive applications and APIs that simply integrate into existing enterprise systems to support business decisions across underwriting, risk selection, mitigation, and portfolio management.
How we understand and manage risk affects everyone and our passion is nothing less than creating a more resilient world through a better understanding of catastrophic events. Join our team of leading scientists, developers, industry experts, and world-class professionals. Together, RMSers make a difference on a truly global scale.
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Sr. Modeling Analyst – Remote Sensing
Department:
Model Development
Objective of the Role:
The candidate will be extensively involved in all the production activities from remotely sensed data and support the integration of resultant products into a GIS environment for exposure models for modeled countries. Maintain and deliver the geospatial data and data components on time with highest quality. Particular skills in programming, numerical/statistical analysis, computing, databases etc. would add value.
Key Accountabilities & Deliverables:
- Overall responsible for quantitative and qualitative analysis of satellite/ aerial images
- Responsible for process enhancement initiative to meet the requirements for exposure models
- Involve in applying geospatial, remote sensing and other supportive domain knowledge in deriving additional data sources for exposure model development
- Establishes credibility by thought partnering on geospatial topics; takes positions and draws conclusions on a range of external and internal issues
- Provide professional skills necessary for all phases of data analysis, including the application of image processing methods for conducting analysis, QA/QC/, documentation and presentation.
- Communicates analytical insights through sophisticated synthesis and packaging of results (Including PPT slides and charts)
- Serve as an active participant on cross-functional projects, interpreting data, and translating into actionable insights, provide support on ad-hoc analysis and reports.
Experience Required:
- Post Graduate in Geoinformatics, Remote Sensing, Earth Sciences or Graduate in Civil Engineering, Computer Science, Environmental Science from an institute of good repute
- 0 to 2 year of total experience in developing geospatial data and data components for catastrophe risk insurance industry
- Research, collect, analyze and consolidate available datasets (Land Use and Land Cover – LULC - layers, building footprints, industrial facility polygons, road networks etc.)
- Analyze remotely sensed data from airborne, satellites, or ground-based platforms, using image processing software, GIS software, or statistical analysis software.
- Knowledge of analysis techniques like statistical methodology, numerical techniques and data manipulation
- Critical thinking skills and hands on experience in data interpretation, formulating hypotheses and being able to make educated guesses when data may be sparse or unavailable
- Strong documentation skills with experience of working on MS Word, Excel (advanced knowledge such as using pivots, filters, using external data etc.), PowerPoint and Project
- Excellent communication skills and ability to independently lead and drive projects
Technical Skills:
- Deep understanding in remote sensing technology (classification, segmentation, change detection, decorrelation algorithms) for identifying the classes/ objects in hyper/multi – spectral satellite/ aerial images
- Strong working knowledge of ENVI and ESRI GIS software products and hands on exposure to open source platform such as QGIS, GRASS etc.
- Familiarity with Google Earth Engine and Open Street Map would be a plus
- Knowledge of analysis techniques like statistical methodology, numerical techniques and data manipulation
- Programming skills in Python, VB.Net, C#, C++, SQL etc will be an added advantage
- Quick leaner for new technologies, programming techniques, languages, and operating systems is a must