Senior Model Quality Analyst II

An ideal candidate for the Model QA Analyst role would have a strong background in mathematics and statistics, along with some programming knowledge. This expertise is essential for understanding the financial losses caused by natural perils like earthquakes, tropical cyclones, and other disasters, as the role involves analysing and validating models that predict such events and their financial impact.

• A bachelor s or post graduate degree in engineering, Mathematics or Statistics with strong credentials.
• 6-8 years of experience in data analytics or catastrophe modelling.
• Proficiency with relational databases (e.g., MS-SQL) and mentoring abilities.
• Experience in analysing and manipulating large datasets.
• Familiarity with statistical and mathematical software (e.g., R, Python) and strong MS Excel skills.
• Knowledge of geo-spatial data processing using GIS software (e.g., QGIS, ArcGIS).
• Strong analytical skills to identify patterns and mathematical relationships in data.
• Experience with probabilistic models in engineering, science, catastrophe modelling, finance, or actuarial science.
• Programming skills in numerical, scientific, and database programming.
• Excellent problem-solving and attention to detail.
• Experience working with global, diverse teams.
• Strong communication skills to work with cross-functional teams.
• Understanding of product development life cycles and the role of quality assurance.
• Logical thinking and process-driven decision-making.
• Strong multitasking abilities with a focus on accuracy and efficiency.

• Reviewing requirement documents to understand what needs testing and the scope of updates for models/products.
• Learning about natural disasters (earthquakes, Cyclone floods etc.) and how they are modelled and predicted.
• Creating and approving detailed test plans, ensuring all aspects are covered based on client needs and model details.
• Executing tests on time and ensuring models are tested delivered with high quality.
• Validating model outputs across different platforms and checking for consistency.
• Analysing model results using statistical methods and ensuring algorithms meet expected standards.
• Ensuring thorough testing of all features and helping new team members get up to speed quickly.
• Presenting test results to peers, estimating project timelines, and managing changes in requirements.
• Handling the hardware and software needs for testing, working with development PO teams to get timely fixes and validate.
• Designing test automation processes and managing the entire testing cycle.
• Providing regular status updates to product owners and helping improve decision-making with clear communication.
• Expanding automated testing practices throughout the project life cycle and collaborating with teams to meet deadlines.
• Managing multiple product deliveries at once and learning new technologies like Touchstone software to improve testing efficiency.