Verified Job
IT / Software / Data Analyst
Computer Scientist
IT / Software / Data Analyst
#739642
Remote / WFH
L&T Technology Services
Job Description
Computer Scientist
Experience - 10-15 Years
Job Location - Bangalore
Quick joiners are preferred
Core Technical Skills
• Strong foundation in Physics, Applied Mathematics, or Engineering principles
• Expertise in statistical modeling and inference
• Develop physics‑based, mathematical, and statistical models to represent real‑world systems and processes
• Experience with numerical methods, optimization, and simulations
• Solid understanding of probability theory and linear algebra
Modeling & Analytics
• Experience with time‑series analysis, stochastic modeling, or Bayesian methods
• Knowledge of model validation, uncertainty analysis, and robustness testing
• Exposure to physics‑informed modeling or hybrid (physics + ML+Deep Learning) approaches
• Ability to work with noisy, incomplete, or real‑world data
• Analyze large, complex datasets to extract patterns, trends, and insights
• Apply regression, classification, time‑series analysis, Bayesian methods, and optimization
• Integrate physics‑informed or constraint‑based approaches with ML models (e.g., Physics‑Informed ML)
Role will be discussed during interview discussion.
Experience - 10-15 Years
Job Location - Bangalore
Quick joiners are preferred
Core Technical Skills
• Strong foundation in Physics, Applied Mathematics, or Engineering principles
• Expertise in statistical modeling and inference
• Develop physics‑based, mathematical, and statistical models to represent real‑world systems and processes
• Experience with numerical methods, optimization, and simulations
• Solid understanding of probability theory and linear algebra
Modeling & Analytics
• Experience with time‑series analysis, stochastic modeling, or Bayesian methods
• Knowledge of model validation, uncertainty analysis, and robustness testing
• Exposure to physics‑informed modeling or hybrid (physics + ML+Deep Learning) approaches
• Ability to work with noisy, incomplete, or real‑world data
• Analyze large, complex datasets to extract patterns, trends, and insights
• Apply regression, classification, time‑series analysis, Bayesian methods, and optimization
• Integrate physics‑informed or constraint‑based approaches with ML models (e.g., Physics‑Informed ML)
Role will be discussed during interview discussion.
