Infosys→
Gen AI Engineer at Infosys in Location not listed
Mid LevelOn-siteNot specified
Job Description
In the assigned Job Role of Data Science Consultant 1, your Area Of Responsibility will be as below:
• Participate in data extraction, transformation, and preparation.
• Resolve common data issues and ensure quality for model development.
• Participate in developing models using statistical or machine learning techniques and collaborate with technology teams to operationalize them into analytics tools or scripts.
• Participate in model testing and validation, selecting the best-performing algorithms based on statistical and business metrics.
• Participate in the development of advanced analytics and machine learning or deep learning models including LLMs using predefined processes and tools like SAS and R/ Python.
• Participate in defining analytics problems; execute visualization, analysis, and predictive modeling with senior support.
• Identify data sources and extract from RDBMS and develop UI/UX for client usage.
• Participate in model performance, while making minor adjustments, and escalate risks or compliance concerns and generate reports on deviations or schedule slippages.
• Proactively participate in detailed documentation of model development, testing, and deployment activities for reproducibility.
• Work closely with business and technology teams to translate requirements into actionable models, while communicating results effectively.
• Apply predefined quality measurement frameworks, if any, to individual project tasks.
• Participate in deploying analytics tools in test and production environment, while ensuring they meet operational requirements.
Your contribution to the team:
• Strong analytical and problem-solving mindset with hands-on model development skills.
• Ability to translate business needs into actionable analytics solutions.
• Focus on data quality, validation and performance optimization.
• Effective collaboration with business and technology stakeholders.
• Commitment to continuous learning, knowledge sharing, fostering team development.
• Participate in data extraction, transformation, and preparation.
• Resolve common data issues and ensure quality for model development.
• Participate in developing models using statistical or machine learning techniques and collaborate with technology teams to operationalize them into analytics tools or scripts.
• Participate in model testing and validation, selecting the best-performing algorithms based on statistical and business metrics.
• Participate in the development of advanced analytics and machine learning or deep learning models including LLMs using predefined processes and tools like SAS and R/ Python.
• Participate in defining analytics problems; execute visualization, analysis, and predictive modeling with senior support.
• Identify data sources and extract from RDBMS and develop UI/UX for client usage.
• Participate in model performance, while making minor adjustments, and escalate risks or compliance concerns and generate reports on deviations or schedule slippages.
• Proactively participate in detailed documentation of model development, testing, and deployment activities for reproducibility.
• Work closely with business and technology teams to translate requirements into actionable models, while communicating results effectively.
• Apply predefined quality measurement frameworks, if any, to individual project tasks.
• Participate in deploying analytics tools in test and production environment, while ensuring they meet operational requirements.
Your contribution to the team:
• Strong analytical and problem-solving mindset with hands-on model development skills.
• Ability to translate business needs into actionable analytics solutions.
• Focus on data quality, validation and performance optimization.
• Effective collaboration with business and technology stakeholders.
• Commitment to continuous learning, knowledge sharing, fostering team development.