Project Role : AI / ML Engineer
Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing.
Must have skills : Python (Programming Language)
Good to have skills : NA
Minimum 3 year(s) of experience is required
Educational Qualification : 15 years full time education

Summary: The Data Scientist focuses on developing and implementing simulation models to replicate and analyze real-world scenarios within the system. Roles & Responsibilities: - Expected to perform independently and become an SME. - Required active participation/contribution in team discussions. - Contribute in providing solutions to work-related problems. - Develop and implement simulation models and algorithms. - Analyze data to identify trends and patterns for simulations. - Collaborate with stakeholders to translate business requirements into simulation models. - Validate and optimize simulation models for accuracy and performance. - Work with other data scientists and engineers to integrate models into the system. - Create a proper cloud or on-prem application pipeline with production-ready quality. Professional & Technical Skills: - Must To Have Skills: Proficiency in Python (Programming Language). - Expertise in simulation modeling and data analysis. - Proficiency with data science tools and programming languages (Python, R, etc.). - Strong statistical and analytical skills. - Experience in data preprocessing and model validation. - Ability to work collaboratively with cross-functional teams. - Experience with data visualization tools such as Tableau or Power BI. - Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms. - Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. Additional Information: - A 15 years full-time education is required.

15 years full time education

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